So first of all, I completely support the HoH podcast and will sign up on Patreon. But I notice that a lot of influencers and podcasts are taking money from Betterhelp, an online therapy platform, including the House of Halliwell.
I used to work for Betterhelp as a therapist, and while their therapists are vetted, I found it to be an exploitative platform. They pay their therapists poorly (Uber model: the people at corporate and tech engineers rake bank while the frontline workers scrape by) and recently had a major privacy investigation. Many of the therapists on there also have to take on ridiculously high client rosters which can hurt quality of care and availability. I was only part-time, but I knew colleagues who took on 50+ clients.
I doubt Holly, Drew, and Brian read this. But just letting folks know so that they avoid signing up.
Mental Health Alternatives to find therapy (it's also mental health month!):

• Open Path Collective (reduced fee therapy for underinsured or uninsured folks)
• Psychology Today
• Therapy for Black Girls
• Therapy for Latinx

Well Uber it’s been fun. I’ve been driving for almost a year now and finding it more and more impossible to make a living wage. At first I liked the connivence of working my own hours on my own schedule but it’s become clear Uber can’t compete with even a minimum wage job.
One of my biggest gripes has been since I moved 3 months ago I haven’t been able to receive boosts or promos in my new region. They accounted for roughly 40% of my earnings in previous markets. After contacting support they said it takes about 3 months for everything to switch over and start receiving boost and quests again (Lyft said the same thing). Since I’m moving again for a new job I would have to wait ANOTHER 3 months in my new location, making it just totally not worth it.
Anyway, heading out to Vegas to be a poker dealer for the summer. STARTING wage is 50+ hr. Good riddance Uber 🖕
EDIT:
World Series of poker dealer pay not supposed to the topic of discussion but since my numbers are causing uproar I want to consolidate my response here.
Ive worked in the casino industry, specifically poker rooms on and off for 6 years. Over that time I’ve averaged 45-60/hr.
The WSOP (World Series of poker) is hiring this summer for 12.50/hr base pay, then 15-20 per down (30 minute blocks dealing at the table) the 15-20 pay depends on if you’re dealing no limit holdem or a more complicated mixed game variant. you normally do 4-5 of these in a row then take a 30 min break and do it again.
This WSOP dealers will make their base rate, plus 2 downs an hour, this will equal, 42.50, 47.50, or 52.50 PER HOUR.
This is not up for interpretation, this is what the job pays.
Please stop with the “but Glassdoor says you only make 10-14” yes that is base rate. Dealers earn tips in cash games and get guaranteed hourly pay (as above) for tournaments such as the wsop.

As an international student, finding the right part-time job can be crucial for covering expenses such as rent, textbooks, and other living expenses. However, it can also be challenging to find a job that fits your schedule, your skills, and your visa requirements. In this blog post, we will explore some of the best part-time jobs for international students.
​
1.) On-Campus Jobs
Many universities offer on-campus jobs to students, such as working in the library, bookstore, or cafeteria. On-campus jobs can be an excellent option for international students because they often offer flexible hours, understanding supervisors, and the opportunity to network with professors and other students. Additionally, on-campus jobs typically do not require a work permit, making them a great choice for international students who have visa restrictions on working off-campus.
​
2.) Tutoring
If you excel in a particular subject, you can offer tutoring services to other students. Tutoring can be a rewarding and well-paying job that allows you to share your knowledge and help other students succeed. You can offer your services through your university's tutoring center or advertise your services through online platforms such as Tutor.com or Chegg.
​
3.) Freelancing
Freelancing can be a great option if you have skills in areas such as writing, graphic design, or coding. Freelancing allows you to work from anywhere and often provides flexible hours. Websites such as Upwork, Fiverr, and Freelancer offer opportunities for freelancers to find clients and earn money.
​
4.) Retail
Retail jobs can provide flexible hours and can be a good way to develop customer service skills. Working in retail can also be a great opportunity to improve your language skills if you work in a store that caters to international customers. Retail jobs can be found at local stores or through online job search engines such as Indeed or Glassdoor.
​
5.) Food Service
Working in a restaurant or café can be a good option if you enjoy interacting with people and have good communication skills. Food service jobs can provide flexible hours and can be found in many different types of establishments, from fast food restaurants to high-end cafes. You can search for food service jobs through job search engines or by asking around in your local area.
​
6.) Delivery Services
With the rise of delivery services, jobs such as Uber Eats or Deliveroo can provide a flexible schedule. Working for a delivery service can allow you to work from your own vehicle or bicycle and can provide a good source of income. However, it is important to make sure that you have the proper insurance and licensing before working as a delivery driver.
​
7.) Call Center Representative
Many call centers offer part-time positions with flexible hours and training. Call center jobs can provide opportunities for language practice and can help you develop valuable customer service skills. Call center jobs can be found through job search engines or by contacting local call centers.
​
8.) Pet Sitting or Dog Walking
If you enjoy being around animals, pet sitting or dog walking can be a great option. You can find clients through online platforms such as Rover or Care.com or by asking around in your local area. Pet sitting or dog walking can provide a flexible schedule and can be a great way to earn money while doing something you enjoy.
​
9.) Event Staffing
Event staffing companies often look for part-time employees for events such as concerts or festivals. Working for an event staffing company can provide a flexible schedule and can be a fun way to earn money. Event staffing jobs can be found through online job search engines or by contacting local event staffing companies.
​
10.) Babysitting
Babysitting can be a good option if you have experience with children and enjoy working with them. Babysitting can provide a flexible schedule and can be found through online platforms such as Care.com or

​

1. Airbnb
2. Uber
3. Coinbase
4. Stripe
5. Zoom
6. Robinhood
7. Palantir
8. Fitbit
9. MongoDB
10. Houzz
11. Square
12. Dropbox
13. Twitch
14. Eventbrite
15. Pinterest
16. SurveyMonkey
17. DocuSign
18. Nutanix
19. MongoDB
20. Atlassian
21. Evernote
22. Glassdoor
23. Robinhood
24. AppDynamics
25. Box
26. NIO
27. Twilio
28. Coursera
29. Udacity
30. Wrike
31. Intarcia Therapeutics
32. DoorDash
33. Flexport
34. GitLab
35. Impossible Foods
36. Paytm
37. Pluralsight
38. Reddit
39. Robinhood
40. ThoughtSpot
41. Udemy
42. Zuora
43. AppFolio
44. Intercom
45. Lightspeed POS
46. PagerDuty
47. Postmates
48. SoFi
49. Weebly
50. ZipRecruiter

What is exactly the work of data science?

Information science keeps on developing as one of the most encouraging and sought-after vocations ways for talented experts. Today, fruitful information experts comprehend that they should propel past the conventional abilities to dissect a lot of information, information mining, and programming abilities. To reveal valuable knowledge for their associations, information researchers should dominate the full range of the information science life cycle and have a degree of adaptability and understanding to boost returns at each period of the interaction. 📷

The Data Science Life Cycle

📷 The picture addresses the five phases of the information science life cycle: Catch, (information securing, information section, signal gathering, information extraction); Keep up with (information warehousing, information purging, information organizing, information handling, information design); Interaction (information mining, bunching/order, information display, information synopsis); Dissect (exploratory/corroborative, prescient investigation, relapse, text mining, subjective examination); Convey (information detailing, information representation, business knowledge, navigation). The expression "information researcher" began as late as 2008 when organizations understood the requirement for information experts who are talented in sorting out and breaking down monstrous measures of data. In a 2009 McKinsey&Company article, Hal Varian, Google's main financial specialist, and UC Berkeley teacher of data sciences, business, and financial aspects, anticipated the significance of adjusting to innovation's impact and reconfiguration of various industries.
“The ability to take data — to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it — that’s going to be a hugely important skill in the next decades.”
– Hal Varian, chief economist at Google and UC Berkeley professor of information sciences, business, and economics
Viable information researchers can recognize pertinent inquiries, gather information from a large number of various information sources, coordinate the data, make an interpretation of results into arrangements, and convey their discoveries in a way that decidedly influences business choices. These abilities are expected in practically all ventures, making gifted information researchers be progressively significant to organizations.

What Does a Data Scientist Do?

In the previous ten years, information researchers have become fundamental resources and are available in practically all associations. These experts are balanced, information-driven people with undeniable level specialized abilities who are fit for building complex quantitative calculations to arrange and blend a lot of data used to respond to questions and drive techniques in their association. This is combined with the involvement with correspondence and initiative expected to convey substantial outcomes to different partners across an association or business. Information researchers should be interested and result-situated, with uncommon industry-explicit information and relational abilities that permit them to make sense of exceptionally specialized results for their non-specialized partners. They have areas of strength for a foundation in measurements and direct variable-based math as well as programming information with centers in information warehousing, mining, and demonstrating to construct and dissect calculations.
📷 Why Become Data Scientist? Glassdoor positioned information researcher among the main three positions in America since 2016.4 As expanding measures of information become more open, enormous tech organizations are as of now not the only ones needing information researchers. The developing interest for information science experts across enterprises, of all shapes and sizes, is being tested by a lack of qualified competitors accessible to fill the open positions. The requirement for information researchers makes it clear that things are not pulling back before very long. LinkedIn recorded information researcher as one of the most encouraging positions in 2021, alongside various information science-related abilities as the most sought after by organizations.

Where Do You Fit in Data Science?

Information is all over and sweeping. Various terms connected with mining, cleaning, examining, and deciphering information are frequently utilized reciprocally, yet they can really include different ranges of abilities and intricacy of information

Data Scientist Information researchers analyze which questions need responding to and where to track down the connected information. They have business intuition and insightful abilities as well as the capacity to mine, clean, and present information. Organizations use information researchers to source, make due, and dissect a lot of unstructured information. Results are then orchestrated and imparted to key partners to drive key dynamics in the association. Abilities required: Programming abilities (SAS, R, Python), factual and numerical abilities, narrating and information perception, Hadoop, SQL, AI Data Analyst Information experts overcome any barrier between information researchers and business investigators. They are furnished with the inquiries that need responding to from an association and afterward arrange and break down information to find results that line up with an undeniable level business methodology. Information investigators are liable for making an interpretation of specialized examination to subjective things to do and actually imparting their discoveries to different partners. Abilities required: Programming abilities (SAS, R, Python), factual and numerical abilities, information fighting, information perception Data Engineer Information engineers oversee outstanding measures of quickly evolving information. They center around the turn of events, sending, the executives, and the advancement of information pipelines and frameworks to change and move information to information researchers for questioning. Abilities required: Programming dialects (Java, Scala), NoSQL information bases (MongoDB, Cassandra DB), systems (Apache Hadoop)

Data Science career outlook and salary opportunities

Information science experts are compensated for their exceptionally specialized range of abilities with serious pay rates and extraordinary open positions of all shapes and sizes organizations in many businesses. With very nearly 6,000 open positions recorded on Glassdoor, information science experts with the fitting experience and training have the amazing chance to transform the absolute most groundbreaking organizations in the world. The following are the typical base pay rates for the accompanying positions:9 Information examiner: $69,517 Information researcher: $117,212 Senior information researcher: $142,258 Information engineer: $112,493 Acquiring specific abilities inside the information science field can separate information researchers considerably further. For instance, AI specialists use significant level programming abilities to make calculations that ceaselessly accumulate information and consequently change their capability to be more successful. 📷

What data scientists really do. According to 35 data scientists

Summary: What do information researchers do? As per interviews with in excess of 30 information researchers, information science is about the framework, testing, and utilizing AI for direction, and information items. Information science is being utilized in various fields, however, it's not about profound learning or the quest for counterfeit general knowledge. The abilities required incorporate correspondence and narrating, truth be told. Yet, information science is turning out to be more specific, and with that, the abilities information researchers need are advancing. What's more, morals are turning into an increasingly big test. Present-day information science arose in tech, from advancing Google search rankings and LinkedIn proposals to affecting the titles Buzzfeed editors run. However, it's ready to change all areas, from retail, media communications, and horticulture to wellbeing, shipping, and the correctional framework. However the expressions "information science" and "information researcher" aren't generally effectively gotten, and are utilized to depict much information-related work. What, precisely, is it that information researchers do? As the host of the DataCamp digital broadcast DataFramed, I have had the delight of talking with north of 30 information researchers across a wide cluster of businesses and scholastic disciplines. In addition to other things, I've gotten some information about what their positions involve. The facts really confirm that information science is a fluctuating field. The information researchers I've talked with approach our discussions from many points. They portray an extensive variety of work, including the gigantic web-based trial structures for item improvement at booking.com and Etsy, the strategies Buzzfeed uses to carry out a multi-equipped crook answer for title enhancement, and the effect AI has on business choices at Airbnb. That last model came during my discussion with Airbnb information researcher Robert Chang. At the point when Chang was at Twitter, that organization was centered around development. Now that he's at Airbnb, Chang deals with productized AI models. Information science can be utilized in various ways, depending on the business as well as on the business and its objectives. In any case, in spite of the assortment, various topics have risen up out of these discussions. They are these: What data scientists do. We presently know-how information science functions, in the tech business. To start with, information researchers lay a strong information establishment to perform powerful investigations. Then, at that point, they utilize online trials, among different strategies, to accomplish feasible development. At last, they fabricate AI pipelines and customized information items to more readily grasp their business and clients and to pursue better choices. As such, in tech, information science is about the foundation, testing, AI for navigation, and information items. Great strides are being made in industries other than tech. I talked with Ben Skrainka, an information researcher at Guard, about how that organization is utilizing information science to upset the North American shipping industry. Sandy Griffith of Flatiron Wellbeing educated us regarding the effect information science has started to have on malignant growth research. Drew Conway and I examined his organization Alluvium, which "utilizes AI and man-made brainpower to transform enormous information streams delivered by modern tasks into experiences." Mike Tamir, presently head of self-driving at Uber, talked about working with Takt to work with Fortune 500 organizations utilizing information science, remembering his work for Starbucks' suggestion frameworks. This non-thorough rundown outlines information science upheavals across a huge number of verticals. It isn’t all just the promise of self-driving cars and artificial general intelligence. A considerable lot of my visitors are distrustful not just of the fetishization of counterfeit general knowledge by the established press (counting titles like VentureBeat's "A man-made intelligence god will arise by 2042 and compose its own book of scriptures. Will you love it?"), yet additionally of the buzz around AI and profound learning. Of course, AI and profound learning are strong methods with significant applications, in any case, likewise with all buzz terms, a sound distrust is altogether. Virtually every one of my visitors comprehends that functioning information researchers make their day-to-day bread and butter through information assortment and information cleaning; building dashboards and reports; information representation; factual derivation; imparting results to key partners; and persuading chiefs of their outcomes. The skills data scientists need are evolving (and experience with deep learning isn’t the most important one). In a discussion with Jonathan Nolis, an information science pioneer in the Seattle region who helps Fortune 500 organizations, we suggested the conversation starter, "Which expertise is more significant for an information researcher: the capacity to utilize the most complex profound learning models, or the capacity to make great PowerPoint slides?" He presented a defense for the last option since conveying results stays a basic piece of information work. Another common subject is that these abilities, so essential today, are probably going to change on a generally short timescale. As we're seeing fast improvements in both the open-source environment of devices accessible to do information science and in the business, productized information science apparatuses, we're likewise seeing expanding computerization of a ton of information science drudgery, for example, information cleaning and information readiness. It has been a typical figure of speech that 80% of an information researcher's important time is spent essentially finding, cleaning, and sorting out information, leaving simply 20% to perform investigation as a matter of fact. Be that as it may, this is probably not going to endure. Nowadays even a lot of AI and profound learning is being computerized, as we realized when we devoted an episode to mechanized AI and heard from Randal Olson, the lead information researcher at Life Epigenetics. One aftereffect of this quick change is that by far most of my visitors let us know that the vital abilities of information researchers are not the capacities to fabricate and utilize profound learning foundations. Rather they are the capacities to learn on the fly and to impart well to respond to business questions, clearing up complex outcomes for nontechnical partners. Hopeful information researchers, then, ought to zero in less on strategies than on questions. New procedures go back and forth, however, decisive reasoning and quantitative, explicit abilities will stay sought after. Specialization is becoming more important. While there is no obvious professional way for information researchers, and little help for junior information researchers, we are beginning to see a few types of specialization. Emily Robinson depicted the distinction between Type An and Type B information researchers: "Type An is the investigation — kind of a conventional analyst — and Type B is building AI models." Jonathan Nolis separates information science into three parts: (1) business knowledge, which is basically about "taking information that the organization has and getting it before the ideal individuals" as dashboards, reports, and messages; (2) choice science, which is tied in with "taking information and utilizing it to assist an organization with pursuing a choice"; and (3) AI, which is about "how might we take information science models and put them ceaselessly into creation." Albeit many working information researchers are at present generalists and do each of the three, we are seeing unmistakable professional ways arising, as on account of AI engineers. Ethics is among the field’s biggest challenges. You might suspect that the calling offers its experts a lot of vulnerability. When I inquired as to whether some other significant difficulties confront the information science local area, she said, "Do you feel that uncertain morals, no guidelines of training, and an absence of steady jargon are insufficient difficulties for us today?" Each of the three is the fundamental focus, and the initial two specifically are the front of the psyche for virtually every DataFramed visitor. When so many of our collaborations with the world are directed by calculations created by information researchers, which job do morals play? As the Omoju Mill operator, the senior AI information researcher at GitHub, said in our meeting: We really want to have that moral comprehension, we really want to have that preparation, and we want to have something much the same as a Hippocratic pledge. Also, we want to really have appropriate licenses so that assuming you truly accomplish something untrustworthy, maybe you have a punishment of some sort or another, or disbarment, or some sort of response, a comment this isn't what we believe should do as an industry, and afterward sort out ways of remediating individuals who run wild and do things since individuals simply aren't prepared and they don't have the foggiest idea.
A repetitive subject is the serious, destructive, and exploitative outcomes that information science can have, for example, the COMPAS Recidivism Hazard Score that has been "utilized the nation over to anticipate future lawbreakers" and is "one-sided against blacks," as indicated by ProPublica.
We're moving toward an agreement that moral principles need to come from inside information science itself, as well as from officials, grassroots developments, and different partners. Some portion of this development includes an emphasis on interpretability in models, rather than black-box models. That is, we really want to assemble models that can make sense of why they make the expectations they make. Profound learning models are perfect at a lot of things, however, they are scandalously uninterpretable. Many devoted, keen specialists, designers, and information researchers are gaining ground here with work, for example, Lime, a task pointed toward making sense of what AI models are doing.
The information science transformation across ventures and society overall has recently started. Whether the title of information researcher will stay the "hottest occupation of the 21st 100 years," will turn out to be more particular, or will turn into a bunch of abilities that most working experts are just expected to have is indistinct. As Hilary Artisan told me: "Will we even have information science in 10 years? I recall an existence where we didn't, and it would make perfect sense if the title goes the method of 'website admin.'"
For more Articles like these visit: Data Science and technology

Exhausted
I am late to the party. I was fortunate to have had financial security during the pandemic, and don't take that for granted. Unemployment was very helpful, and paying over $800 back that tax period sucked, but it was better than starving. I have no more unemployment available.
A month ago, I was working for a coop. Details set aside I quit before they terminated me that day. I stood up for myself as a supervisor, and refused to take abuse for my manager failing to do her end of the work. There was an unspoken rule of supervisors doing manager level pay, so the wouldn't have to bring an assistant manager on board/ give me a raise.
As a business, okay. I see why you wouldn't want to promote someone if you can make them work for less pay until burnout, then replace them. This is a common practice.
I have applied to over 530 different jobs in the past month. I have used everything from Indeed, Glassdoor, local job works boards, etc. At my prior job I was at 17.25.
Fast forward to a week into being unemployed, I was offered a VERY sketchy job. I had already been harassed within 10 minutes of being toured around the establishment, (by current BOH staff, and the manager interviewing me laughed nervously when the harassment happened. It was clear the manager had no idea the names of anyone around him, and the air turned to ice when he approached any staff member.
I had 3 job interviews that same week, and went to 1 of them. The other 2 interviews had contradictory locations. The application said one thing, the recruiter another.(This has happened roughly 7 times so far in my interviewing process) I don't drive, and rely on public transit, which has gone to shit since the pandemic.
So that remaining interview in week 2, the manager made me wait 45 minutes, (which okay fine, you must be busy?) and proceeded to not pay attention to anything I was saying, got up for like 5 minutes to go help a staff memeber, came back, and proceeded to turn around, doze off into space, come back and retort "Sorry, im distracted easily."
After the interview, he offers me the job. It took him 4 weeks to send the offer letter. Alongside the offer letter, he tells me his locetion doesnt need anyone, and they have a store 45 minutes away that could use me. I explained to him I dont have the ability to make it there, and he tells me they can pay "cash only" uber and lyft reinbursment. I ask him more details, and he said he couldnt tell me more. So I asked if it would be easier to ask someone else, and he tells me I ask everything through him, and everything I have goes to him because he was my "main store".
I accepted the offer letter, because I needed the job. He ghosted me. I reached out multiple times and no one has said anything to me.
Update: Its been about 3 weeks of ghosting, and the manager messages me, and says hes sorry for taking so long to respond, and If i am ready for onboarding. ????????????
Coming up onto now, I had 7 job interviews. 5 of them were the same issue I had in the beginning. Says one location, comes back to offer the interview, and they want me to meet them an hour out,because thats actually where the workplace is.
I did the two job interviews this week. Both said they would get back to me, and both have reached out saying no.
I have a relatively solid resume, reference list, and have been doing everything I thought I was suppose to be doing right.
I Support a household, and am now about to have my utilities shut off.
Am I really that bad of an employee? Ive never had to look longer this long for a job with my level of experience.

Let's get real; we know how disheartening it can get to build your dream startup in the recessionary times, but with technology by your side, trust us that the war is not yet lost.
Here's how investments in technology recession-proof your startup:
1. Technology Reconditioning
Meeting a user's needs at a lower cost by employing technology.
Pro Tip: Take an area where consumers spend heavily during healthy economic times and meet the same need at a lower cost during these turbulent times.
2. Solidifying Customer Relations
Technology helps personalize the customer experience and serve customers better. Leverage on that!
3. Enhancing Efficiency
Technology enhances internal processes, so less time and money are spent on the mundane and more on high-value processes that directly affect the bottom line.
4. Boosting Sales and Productivity
Assess your sales challenges and enable better data ownership through technology.
5. Disruption-proof Your Business
AI and ML ensure low error and high productivity, and IoT makes seemingly disparate data sources coherent and leads to several use cases in industries.
So technically, technology can be the savior you are looking for in this Recession!
And just to build your confidence further, Whatsapp isn't the only one; Uber, Airbnb, Mailchimp, Glassdoor, and many more.
The list is long; you might want to google it yourself. Once you are done, get back to building your startup. Good luck! :)

Let's get real; we know how disheartening it can get to build your dream startup in the recessionary times, but with technology by your side, trust us that the war is not yet lost.
Here's how investments in technology recession-proof your startup:
1. Technology Reconditioning
Meeting a user's needs at a lower cost by employing technology.
Pro Tip: Take an area where consumers spend heavily during healthy economic times and meet the same need at a lower cost during these turbulent times.
2. Solidifying Customer Relations
Technology helps personalize the customer experience and serve customers better. Leverage on that!
3. Enhancing Efficiency
Technology enhances internal processes, so less time and money are spent on the mundane and more on high-value processes that directly affect the bottom line.
4. Boosting Sales and Productivity
Assess your sales challenges and enable better data ownership through technology.
5. Disruption-proof Your Business
AI and ML ensure low error and high productivity, and IoT makes seemingly disparate data sources coherent and leads to several use cases in industries.
So technically, technology can be the savior you are looking for in this Recession!
And just to build your confidence further, Whatsapp isn't the only one; Uber, Airbnb, Mailchimp, Glassdoor, and many more.
The list is long; you might want to google it yourself. Once you are done, get back to building your startup. Good luck! :)

Let's get real; we know how disheartening it can get to build your dream startup in the recessionary times, but with technology by your side, trust us that the war is not yet lost.
Here's how investments in technology recession-proof your startup:
1. Technology Reconditioning
Meeting a user's needs at a lower cost by employing technology.
Pro Tip: Take an area where consumers spend heavily during healthy economic times and meet the same need at a lower cost during these turbulent times.
2. Solidifying Customer Relations
Technology helps personalize the customer experience and serve customers better. Leverage on that!
3. Enhancing Efficiency
Technology enhances internal processes, so less time and money are spent on the mundane and more on high-value processes that directly affect the bottom line.
4. Boosting Sales and Productivity
Assess your sales challenges and enable better data ownership through technology.
5. Disruption-proof Your Business
AI and ML ensure low error and high productivity, and IoT makes seemingly disparate data sources coherent and leads to several use cases in industries.
So technically, technology can be the savior you are looking for in this Recession!
And just to build your confidence further, Whatsapp isn't the only one; Uber, Airbnb, Mailchimp, Glassdoor, and many more.
The list is long; you might want to google it yourself. Once you are done, get back to building your startup. Good luck! :)

Let's get real; we know how disheartening it can get to build your dream startup in the recessionary times, but with technology by your side, trust us that the war is not yet lost.
Here's how investments in technology recession-proof your startup:
1. Technology Reconditioning
Meeting a user's needs at a lower cost by employing technology.
Pro Tip: Take an area where consumers spend heavily during healthy economic times and meet the same need at a lower cost during these turbulent times.
2. Solidifying Customer Relations
Technology helps personalize the customer experience and serve customers better. Leverage on that!
3. Enhancing Efficiency
Technology enhances internal processes, so less time and money are spent on the mundane and more on high-value processes that directly affect the bottom line.
4. Boosting Sales and Productivity
Assess your sales challenges and enable better data ownership through technology.
5. Disruption-proof Your Business
AI and ML ensure low error and high productivity, and IoT makes seemingly disparate data sources coherent and leads to several use cases in industries.
So technically, technology can be the savior you are looking for in this Recession!
And just to build your confidence further, Whatsapp isn't the only one; Uber, Airbnb, Mailchimp, Glassdoor, and many more.
The list is long; you might want to google it yourself. Once you are done, get back to building your startup. Good luck! :)

Let's get real; we know how disheartening it can get to build your dream startup in the recessionary times, but with technology by your side, trust us that the war is not yet lost.
Here's how investments in technology recession-proof your startup:
1. Technology Reconditioning
Meeting a user's needs at a lower cost by employing technology.
Pro Tip: Take an area where consumers spend heavily during healthy economic times and meet the same need at a lower cost during these turbulent times.
2. Solidifying Customer Relations
Technology helps personalize the customer experience and serve customers better. Leverage on that!
3. Enhancing Efficiency
Technology enhances internal processes, so less time and money are spent on the mundane and more on high-value processes that directly affect the bottom line.
4. Boosting Sales and Productivity
Assess your sales challenges and enable better data ownership through technology.
5. Disruption-proof Your Business
AI and ML ensure low error and high productivity, and IoT makes seemingly disparate data sources coherent and leads to several use cases in industries.
So technically, technology can be the savior you are looking for in this Recession!
And just to build your confidence further, Whatsapp isn't the only one; Uber, Airbnb, Mailchimp, Glassdoor, and many more.
The list is long; you might want to google it yourself. Once you are done, get back to building your startup. Good luck! :)

Interested in a career in data science? Data science is a lucrative, in-demand, and steadily expanding field, you'll find that all leading resources and authorities share this prediction. In fact, data scientists have been named the "number one job in America" and around the world. For four out of the last five years, they are still in third place today, according to Glassdoor. Data science is referred to as "the sexiest job of the 21st Century" by Harvard Business Review. Supermodels and rock stars, get out of here.
What about data science makes it such a hot field to enter? Let's concentrate on the top five that the study has shown to be motivating as an introduction to a lengthy list of reasons:

But First, Who is a data scientist?

It's worth spending some time on the specifics of this career path before we respond to the topic of why you should become a data scientist.
Data scientists are required to possess experience across a variety of fields simultaneously. They are a combination of mathematicians, computer scientists, and business strategists. Data scientists must continually have one foot in the information technology industry and another firmly planted in the business world because of their complicated skill set. That's one of the reasons why data scientists are one of the best job choices you can choose, given their high demand.
A good data scientist must have both the statistical understanding and computer abilities required for solving complicated problems because data science is largely focused on deep knowledge discovery through data exploration and inference. This field focuses on employing mathematical and algorithmic tools to address some of the most analytically challenging business issues, using vast amounts of unprocessed data to uncover the hidden knowledge that lies under the surface. To become a skilled data scientist, join the best data science course, by Learnbay and earn certification from IBM.
The heart of the data science discipline is focused on accurate and frequently detail-oriented analysis, developing strong decision-making talents, and is occasionally a solitary and silent one. Data scientists are expected to communicate their findings and analysis to their superiors, coworkers on different teams, and company stakeholders who may or may not be able to understand complex statistical jargon. As a result, data scientists must also have exceptional verbal, written, and visual communication skills. Data scientists must communicate what they have learned, how they know they have learned it, and what should be done with the knowledge now that it is thoroughly and understandable. Often not an easy task.
A data scientist may be extracting data from a database, getting the data ready for different analyses, developing and testing a statistical model, or producing reports with understandable data visualizations on any given day. While data science projects and activities may vary based on the organization, some fundamental job responsibilities are typically shared by all data science positions, such as:

1. Collecting enormous amounts of data and transforming it into a format that is easy to analyze.
2. Overcoming issues in the corporate world using tools and tactics powered by data.
3. Using a range of programs and programming languages for data collection and analysis
4. Possessing a lot of expertise in analytical methods and tools.
5. Delivering results and guiding through impactful data visualizations and thorough reports
6. Recognizing patterns and trends in data and offering a plan to implement improvements.
7. Predictive analytics; foreseeing upcoming needs, occasions, performances, trends, etc.
8. Contributing to data analysis, reporting, and modeling methodologies used in data mining.
9. Creating innovative algorithms to address issues and create analytical tools.
10. Recommending reasonable adjustments to current practices and tactics.

You can explore Learnbay’s data science course online if you're interested in learning more about what a career in data science includes. We advise analyzing these top 5 reasons to enter the profession if you're still considering pursuing a career or school in data science.

Reason #1 – Make a Significant Impact on Your Business and the Environment

The impact you can have as a leader in the field, both within your firm and in the rest of the world, can be one of the most compelling (at least globally) reasons to pursue a career in data science.
You can try to automate laborious operations within your firm, saving the business time and perhaps thousands or even millions of dollars they could otherwise allocate to other projects. We'll go through how businesses in contemporary industries are well aware of the immense value that their data scientists offer and how heavily they rely on them. Data scientists are thus well positioned to serve as enterprises' go-to strategists, whether they work for a tiny start-up or a global powerhouse like Amazon, Apple, or Uber. All of them are constantly looking for qualified data scientists.
Although many data scientists work in the financial business or for large IT companies, there are many other industries where you can apply your expertise. Understanding human nature is where data scientists spend most of their time, looking at what makes people tick and why they don't. There isn't a single area out there that doesn't have a pressing need for someone with that kind of skill set, even those that are exciting to work in, like professional sports, the beauty, and cosmetics industry, or the entertainment industry.
The potential for using data science to change the world is even greater. Uninformed individuals could believe that the position comprises being a glorified number cruncher. Although there will undoubtedly be some of that in a typical day, there is considerably more potential value for data science outputs than is generally believed. How you make a difference in the world as a data scientist mostly depends on your passion and the areas where you want to leave your mark.
Dedicated to halting the disastrous effects of climate change? As a data scientist, you might develop more precise weather forecasting and climate models, save lives, or work on cutting-edge public transportation initiatives that reduce CO2 emissions. Do you want to battle hunger? To assist farmers in producing more food, you might examine farming methods and crop yields. Small family farms may be able to save money and maintain a profitable operation. Data scientists contribute to the development of new pharmaceuticals and medical technology, the prevention of blindness, the treatment of cancer, and the empowerment of the underdeveloped globe.

Reason #2 – Increasing Demand

For much of the last decade, data science has been one of the most in-demand professions. In 2022, this trend shows no signs of slowing down at all. In fact, the U.S. Bureau of Labor Statistics predicts that through 2026, employment in the field of data science will increase by 27.9%. In 2018, LinkedIn estimated a shortage of nearly 151,000 data scientists nationwide, with the New York City, San Francisco, and Los Angeles metro areas suffering the most.
So what is it about data science that makes it such a sought-after career? Consider the most powerful and influential businesses on the planet. You probably immediately thought of well-known companies in the sector like Amazon, Google, Apple, or Facebook, whose success is fundamentally dependent on making decisions using data.
Amazon recommends products to customers based on their past purchases and browsing habits using data analytics to power sales and marketing algorithms. Google Search uses data to evaluate web pages' rankings and SEO value, determining both the user experience of online assets and content accessibility. Apple bases its product decisions on how and when you, the customer, use your iPhones, iPads, Macbooks, and other gadgets. Facebook uses data to display highly relevant advertisements to you and facilitate interactions between users and communities. All of these and other decisions are influenced by the data we collect, and data scientists are in charge of influencing those decisions.
Today, a firm almost cannot exist without implementing a data-driven strategy and developing it based on popular applications. The demand for data scientists is still outpacing the supply, thus there is a need and a tremendous opportunity in the sectors related to data science. However, the supply of data scientists continues to be rather low. It's still a rather fresh and developing field even in 2021. Data science can't always say the same, but other 21st-century professions like web design and programming have already begun to make their way onto the curricula of traditional educational systems. The value of data science and its ubiquity in global enterprises, daily community operations, and "corporate America" are vastly different from the existence or comprehension of data science in basic school education. This is beginning to shift, particularly in undergraduate and graduate degree programmes, but it hasn't yet reached a tipping point. The demand for data scientists still appears to outpace the supply of seasoned data scientists in the market.
All of this might make the idea of becoming a data scientist seem a little intimidating, but on the contrary, students or potential employees who choose to pursue this undeniably advantageous field are securing their status as sought-after contributors and "experts" in a top modern workforce that shows no signs of attrition. Successes in data science are remarkably accessible, regardless of whether you are new to data or committed to putting in the effort necessary to put yourself in the lead in a leading business. A way to start is with a bachelor's degree (or even better, a master's degree or PhD) in a subject like math, statistics, computer science, or engineering, along with expertise in SQL and machine learning. As a data analyst, you might need to start out in an entry-level position, but with a skill set as in-demand as data science, you'll have the opportunity to advance, and after you've proven you can do the job, you'll have your pick of top employers and jobs in the field.
Hope you liked this article on key reasons why to become a data scientist. You can continue reading the 2nd part in the next article. To head start your career in data science, you can check out the online data science course, co-powered by IBM. It’s a complete boot camp for working professionals wanting to upgrade their skills.

Part 2 is live. It's aliveeeeee.

Fancy saying with warning for dramatic effect

There are no absolutes in software development. Anyone who claims as such is wrong.
Warning: If you find my writing insufferable, just goto the resources section and read those books.
This post will be all over the place because I am writing this after staying awake for 48 hours with my adhd peaking. too If you want to ,understandbly , avoid the rambling of a guy high on insomnia, goto the resources section and read the books there. They explain these concepts much better than me.

Prologue

Nothing much really. Just wanted to share some advice, world-weary knowledge, rants and some tips sprinkled with bad humour for the juniors in this sub.
None of this is tech heavy so don't worry if you need to do an AWS associate certification course.
The idea of this post is to provide freshers and even people new to software engineering, certain gyaan from someone with experience (relatively) and to provide some advice developing yourself. on how to grow in their career.and actual talk about what career growth means.
Second warning: This rahul dravid post is massive and also contains bad humor and lot of formatting errors. There's a TLDR at the end for people who want a short answer for career success.

What this post (and others) can't answer

Let me get this out of the way. No, I can't answer if your 200% hike on job switch is a bad deal or if it's worth learning MEANIES stack for full heap role in EU or if you can get fully remote coding job with your nietzschean philosophy degree or if going to a tier 3 LKG school now affects your placement chances in 2040.
My answer to the above questions and what I recommend you give as the answer too when asked is: "It depends. Please provide more context and what research you have done on it beforehand".
Everyone has their individual situation and context that will have a lot of variables and the advice strangers give you on the internet for such questions will not apply 1:1 to your situation.
I'll explain the general Q&A trend I have seen on this sub and how unproductive it is for everyone involved.
Asking "How much does full stack developer job pay in bangalore for 2 year experienced guy" will mostly have answers like this, ordered by upvotes.

• 50⬆ user1: 10L
  • 2⬆ OP: thank you
• 30⬆ snarky_user: you'll getting more than 6L?
• 20⬆ user2: bro apply for amazon. my friend interviewed and got 50L offer
  • 30 ⬆ user3: pro tip. don't join amazon.
    • 2⬆user2: why?
    • 0⬆user4:how to prepare for oa test?
  • -1⬆user5:How to apply for amazon?
  • 0⬆ user6:Can you share what you did
• 5⬆user9 : it depends on the companies you are applying to and the expectations for that role. check on salary sharing websites like glassdoor or ask in blind for bigger companies.

Even though OP's question had multiple answers, it ultimately resulted in close zero collective knowledge gain.
OP got to know one figure but not the methodology or reasoning behind it. Usual go FAANG, no FAANG bad bs. And one practical user who has said check salary sharing sites but not getting any follow-up or further discussions on it. Even the passive lurker, i'm looking at you dear user, who is reading it, gains nothing.
You are not sure if these values given by the commenters are accurate and you have already got tired of naagin dance so it doesn't interest you. You are also not interested in going to some website and setting up an account to access data. No , you want the data now, presented neatly in an infographic and in an immediately consumable form. Since we don't have that, you push the information about those sites to the back of your mind and it waits there until the next salary question thread and the cycle repeats.
Now this might seem like me just bitching about these threads but no my dear reader. We are software developers. Problem solving is our forte and we can treat this like a software design problem.
My elaborate rant about the questions can be considered the Problem Statement and The Current State of the System.
So stupid questions are bad and don't increase the knowledge of everyone involved. So we decide on the Requirements and subsequently the Solutions and Reviews..
Our requirements are gonna be pretty simple. Users must do their due diligence on the question first and then ask it.
This should results in the comments of the post taking an indepth look and validating OP's reasoning and conclusion. If OP's methodology is flawed, users can say it is flawed because of X reason instead of the blanket answer we have currently. If it's right, we can vet it and voila either way everyone involved has gained and propogated new knowledge, including you the lurker.
So for all inquisitive software engineers out there, do your due diligence and research on your questions and come up with your own reasoning and conclusions which you can then review with peers and seniors for a productive discussion.

WFH is bad and here's why.

Clickbait heading. While WFH comes with many benefits and might be the best way to work for some folks, it has definitely affected how freshers are developing in a new workplace and it can affect their growth , especially on things which experienced folks know but aren't documented.
In the current remote setting, a fresher can get the developer onboarding wiki, KT on their service or product and even tech stack walkthroughs by their mentosenior.
Let's go ahead and say that there already is extensive documentation or video that the seniors recorded for an earleri onboarding which they recommmend the fresher to watch and subsequently ask if they have any doubts. It makes sense from the senior's perspective as they have already covered the main talking points in that video. So the fresher learns all about the stack, the team's processesand the service thanks to the excellent documentation and the mentor is also helpful in answering questions.
Everything looks great till now, fresher has gained knowledge on the tech stack, and they have a guide they can follow for onboarding to the code base and they also start getting ready to contribute to their team tasks.
All good things from the perspective of everyone involved. The manager, the mentor and even the fresher.
What's the problem then?
This onboarding for the fresher likely only covers things that can help the developer contribute to their teamwork. A lot of the other small but important things get easily missed or dropped in this remote era where everyone hates ad-hoc discussions, extended meetings and long discussions on non-productive tasks.
Let me clarify, i'm not talking about off work hang outs or general fraternization with co-workers. I'm talking about the intristic knowledge transfer that happens in-person for these soft skills and how coffee conversations can flow from topic to topic naturally.
I'm talking about those times when we went for a snack break, started discussing on tata releasing a new car and how it's costly, to talking about quality control and how it affects the cost and then talking about how important it is in tech also to talking about a previous production outage which we might maybe probably been our fault and how it caused the company to setup guard rails and auto pipeline reverts and then talking about the hassle of rolling back partial deployments and trouble identifying what failure metrics to track and then eventually settling back into our seats.
And between all this, the freshers stay quiet until we ask them if they know what we are talking about and then us explaining these things briefly and then telling them to lookup articles or books on this and learn about it and eventually the freshers mind opens up to the bigger picture and they become active participants in the conversation.
All developers at a point in time in their career have been inspired by how their seniors have thought and worked during collaborations or discussions. Seniors influence juniors even extends to their preferences for vim or emacs or notepad (heathens).
A fresher can easily absorb this during office by how their senior works and this leads to inspirations or adaptations of the same process. It could be even be very simple things that are adopted like that moment when the senior tries open iterm but it's not installed and you are asked why you are using the default terminal and tells you to install iterm with custom zshrc commands for ease of use. Or even like the moment where senior comes to help you debug code and then instanly opens the class and line of code without using the touchpad. You know that look on the freshers face when he realizes that he didn't need to manually go through the package explorer everytime to get to the class and he quickly adopts it and even spreads it to his peer group thus increasing collective knowledge.
All of the above can still be explained over a remote setting, but then a lot of the above are unlikely to come up naturally and even most onboardings don't have things like shortcuts because IDE is dev choice.
Another drawback in a remote setting, it becomes hard to initiate discussions like the coffee conversions because no one wants adhoc calls on non-productive talks.
The final major drawback in a remote setting is that the mentor and mentee relationship has a tendency to become very formal and work oriented. Like i rarely crack sarcastic jokes in a remote setting as it can be inferred as serious compared to an inperson meeting where you body language gives it away. Not saying that sarcastic jokes are necessary or anything but since the senior is only matter of fact, the fresher might assume that they are very professional and can't be disturbed for any doubts and so they become hesitant to discuss non-work career growth in detail.
Okay there are some drawbacks for freshers but remote work is a realiy. We can't force people to come to office for coffee talks and onboardings. So what can you, a fresher, do so that you can get to know these intrinsic learnings which are incidental?.
Good question and I have an answer for you. You as a fresher, can easily develop or start developing such habits and this step can also help you address career questions you might have. It's really an all in one, all encompassing step. It's very simple really. You just have to.....

Take ownership of your career

What a vague and unhelpful statement. Put your pitchforks down and let me explain in detail.
You,dear reader, you alone, are the owner of your career. You are the main driver for your career decisions and you should be the one who needs to be pragmatic and start asking the right questions in the right way for everything.
If you don't ask the right questions and rely on others for answers, you start losing ownership of your career and are now relying on others to decide the career path for you.
Note the emphasis on decide. My main point is not to listen to others, it's the exact opposite. You want to know what you don't know and you can only do that by putting in effort. So in order to know what you don't know, you need to learn to question.
Sounds a little confusing I know but bear with me. I'll describe my definition of software engineering and we can learn how to question and pick it apart the right way and then we'll touch up on how it will help your ownership.
And randomly from nowhere comes 🦆-chan. 🦆-chan is gonna be your best friend from now on and they'll help you learn to ask the right questions.
Now for this learning to question exercise, I want you to work in a pair with 🦆-chan. They might not speak much as they're a little shy and it's basically a 2d image but hey, they are your best friend so you have to converse on behalf of them too.
So listing the rules for the excercise,

1. You and 🦆- chan have paried up to ask why? on the given statement.
2. One person will ask the why question and the other emoji has to give an answer to that question.
3. You then start asking why on the answer and so on till a point where you can't or shouldn't ask why.
4. 🦆-chan is shy so when they need to answer a question, you do it in their place. So you'l be talking to yourself. Interesting idea ain't it?
5. If the 🦆-chan or their representative mouthpice(i.e you) don't know the answer to the question, you can consult Google senpai for the answer
6. On the extremely offchance that google senpai doesn't have an answer, you can consult any senior you think might know the answer directly or will know the way to the answer, i,e pointing you to ask that person. Eventualy you'll reach the place where someone can give a definitive answer to the question why?.

Seeing so many steps, your'e probably asking, "Why?". Which is great because that's exactly what we need. The answer will come to your mind after the exercise.
Why? Why? Why? Why? Why?

Statement-1

Software engineering is about solving human problems through software with proper understanding and methodology and at the right abstractions.
Okay my dear reader, let's start off this riveting exercise. Come up with a list of why questions on the above statement and also come up with answer to that why question on 🦆-chan behalf. Take you time . And once you are done, go through the spoiler sections, First and second sections will only be there for the first why as references.
First why
First section: Why? even ask these questions.
If your answer to any of the questions in the section was, why ?, Why even ask this?. What's the benefit you are getting?, Why would you even ask someone that? Then Congrats. You have cleared the first hurdle of not asking obvious questions or questions that give irrelevant information. Such type of questions are asked for the sake of it or asked without any critical thinking. Don't ask such why's to anyone. You can and should ask these type of questions to 🦆-chan and then answer to yourself on their behalf.
​
Q1: Why?
A1: What do you mean why?. It's a statement definition for software engineering. What response are you trying to get?.
Q2: Why only human problems?
A2: Okay software can be used to solve non-human problems too but software is made by humans for humans. Even software for non-human problems would invole a human problem. Why even question this?
Q3: Why proper understanding? or any of the other stupid question
A3: Why even ask this? Problem solving requires understanding of the problem. Really don't need to ask why?
​
Second section: I am whylocked ?
These are questions which have answers that are less obvious but still can be reasoned out through discussions with 🦆-chan .
.Q: Why call it Software Engineering? Why not call it software creationing?
A: On the uber level both software engineering and software creationing seem to just be about creating software. But if you just compare the terms themselves, Engineering is all about working in a process where you design, develop, test and release something. There is a stuctrued process and methodology you follow where as software creation doesn't really define it to be a structured even though it could be..
Alternate A: Who cares about what term is used? We are still creating software to solve problems.
Alternate A follow-up Q: Calling it engineering implies a structured process so we need to call it Software Engineering to emphasize that.
Alternate A follow-up Q A: But the statement already mentions that a certain methodology should be followed. So regardless of what it's called, you need to follow a standard process.
​
Both of the above answers are acceptable. The first one is more academic and technical in nature focusing on the etymology. Basically a semantic nitpicker. The second is more focused on practicality over worrying about the minor details. Both answers understand the requirement for software development to be structured,
Also calling software engineering engineering and whethers it s a craft is a can of worms i don't want to open. Programmers worry too much about semantics and naming unlike us software developers.
​
Third section: The actual good why questions.
Questions you can somewhat deduce but a senior can explain the concept much better. The right kind of questions.
Q: Why do we care about the "right" abstractions?. Why do we even care about abstractions in the first place?
>! Deduced A: Abstraction is the process of removing details you don't need and only focusing on the things you are interested in. So it's probably included because we need to know that the abstractions we are working are correct for the software we are writing.!<
Senior A with examples: Abstractions and the ability to abstract things is a fundamental requirement for a good engineer. Abstractions are not only about removing details but also understanding what matters when and to whom.
Abstraction happens at every level in Software Engineering and it is a very important trait that all developers need to improve as theircareer grows.
So dear reader,as part of this excercise we have asked a definitive why question and reached a statement. What futher questions can you ask on this statement?

Statement-2

Abstraction happens at every level in Software Engineering and it is a very important trait that all developers need to improve as the career grows.
Second why:
Q: Why should all developers care about the design and abstractions for their career? It's not needed for someone to do their work.
A: A valid point. You don't need a software engineering degree to learn coding and grow. There are many great coders who learn through bootcamps wtihout going through a software engineering degree. However abstraction as a concept is not related to the engineering degree. Its your ability to see the bigger picture and ability to focus on the details you want.
​

Statement-3 -

However abstraction as a concept is not related to the engineering degree. Its your ability to see the bigger picture and only focus on the details you want. It is neeeded regardless of your background for career growth.
​
Q: Why would a fresher need to worry about the bigger picture when they just need to focus on learning tech and doing their tasks.
: The fact that the fresher doesn't need to worry about the bigger picture is exactly the point of abstraction. In this case, their team lead abstracted out the larger complicated details and gave them only a small piece of the puzzle to focus on. Eventualy the rookie needs to start looking at the bigger picture so that they can do it it for their own reports as their team lead did for them.
This is precisly why you need the right level of abstraction. Too big and you lose track of what is going on and too small means you are wasting time on nitpicky details. Getting to the right level of abstraction requires critical thinking and good reasoning and a pragmatic mindset. The process of which i'm explaining in this long ass post.

Statement-4 - Senior Answer

Getting to the right level of abstraction requires critical thinking with good reasoning and a pragmatic/practical mindset
Q: What do you mean by having practical mindset? All developers try to be practical only na?, what do you mean by this?
A: Good question. This is a great example of the critical thinking and reasoning practice that freshers need to develop. Now why did I mention the word practical?. Primarily because you need to think from a real world and business persective. Developers are very practical but there are times where they might fuss over some implementation details which might seem important to them but will see zero business impact. So freshers need to strat a habit of thinking from the business perspective along with tech perspective in their career.

Statement-5 - Senior Answer

So freshers need to start a habit of thinking from the business perspective along with tech one in their career.
Q: Why should freshers care about business details? We can spend our time better understanding upcoming technology or frameworks and become an expert there.
A: Why indeed my dear felllow. Apply the five whys on that technology statement and you're on the path to becoming a better developer.
Q. Why do you want to learn the latest and greatest tech framework?
A. Because it's in demand and has lot of job opening.
Q. Why is it in demand?
A. Because it has these cool new tech features that are amazing for developers to use and allows for faster and more robust development.
Q. Why do we need faster and more robust development?
A. Because it allows developments team to release the projects faster for customer. Which improves the business.
See how all the tech framework talk eventually led back to the business?. That's the crux of software development. Cool tech and features are created as a response to business requirements. There is no company which works on cool tech for the sake of it.
Google is so cool they developed big table which led to hadoop. Yeah because they had a business requirement for large scale analytics of data and they were working to solve that.
AWS is so huge right now almost half the web goes through it. Yeah and it was developed internally first as a solution to developer productivity observations.
So all these cool tech mumbo jumbo, ML/AI/ ZZ, cloud certifications and all of those things you hear about from tech gurus. You shouldn't worry too much about it. Learn to abstract them out and you'll see their business case and how it led to that tech existing. Then you'll know if that tech is actually good or if its snake oil.
Now focusing abstraction and design doesn't mean you stop working on lower details. You still do, you're just not tunnel visioned into some framework or tech stack without the bigger picture understanding first.
Now my friend, I hope you have gained a little spark in your mind on the critical reasoning aspect and why it's important for your career. Just reasoning out the existing situation around critically would give you some insights.
So when evaluating your career path and choices, don't get obsessed over the buzz words and demand for x framework or some other bullshit that is thrown around. Start your questioning on the lines of, what are the things you don't know that these guys know?. You'll then eventually find out the actual reason and then you make the decision of moving your career in that directon or not. Don't let others influence your career path without doing due diligence and research.

So what taking ownership really mean

Don't really need to spell it out at this point no?. Do your due diligence, ask the right questions and continute to generate more and more value in your job.

TLDR-FAQ with Rant and resoucres here in part-2

EDIT: Here's a link to how I used notion to prepare my interview notes + a link to the notion notes is available in the description too. If you found this useful please drop a subscribe it'd mean the world to me. https://www.youtube.com/watch?v=GyH6nuwluCI&t=43s&ab_channel=LeonChlon
Organisation is Key
I’ve interviewed at Google (and DeepMind), Uber, Facebook, Amazon for roles that lie under the “Data Scientist” umbrella and this is the typical interview construction theme I’ve observed:
Software Engineering Applied Statistics Machine Learning Data Wrangling, Manipulation and Visualisation
Now nobody is expecting some super graduate level competency in all of these topics, but you need to know enough to convince your interviewer that you’re capable of delivering if they offered you the job. How much you need to know depends on the job spec, but in this increasingly competitive market, no knowledge is lost.
I recommend using Notion to organise your job prep. It’s extremely versatile, and enables you to utilise the Spaced Repetition and Active Recall principles to nail down learning and deploying key topics that come up time and time again in a Data Scientist interview. Ali Abdaal has a great tutorial on note taking with Notion to maximise your learning potential during the interview process.
I used to run through my Notion notes over and over, but in particular, right before my interview. This ensured that key topics and definitions were loaded into my working memory and I didn’t waste precious time “ummmmmm”ing when hit with some question.

1. Software Engineering Not all Data Scientist roles will grill you on the time complexity of an algorithm, but all of these roles will expect you to write code. Data Science isn’t one job, but a collection of jobs that attracts talent from a variety of industries, including the software engineering world. As such you’re competing with guys that know the ins and outs of writing efficient code and I would recommend spending at least 1–2 hours a day in the lead-up to your interview practicing the following concepts:

Arrays Hash Tables Linked Lists Two-Pointer based algorithms String algorithms (interviewers LOVE these) Binary Search Divide and Conquer Algorithms Sorting Algorithms Dynamic Programming Recursion
DO NOT LEARN THE ALGORITHMS OFF BY HEART. This approach is useless, because the interviewer can question you on any variation of the algorithm and you will be lost. Instead learn the strategy behind how each algorithm works. Learn what computational and spatial complexity are, and learn why they are so fundamental to building efficient code.
LeetCode was my best friend during interview preparation and is well worth the $35 per month in my opinion. Your interviewers only have so many algorithm questions to sample from, and this website covers a host of algorithm concepts including companies that are likely or are known to have asked these questions in the past. There’s also a great community who discuss each problem in detail, and helped me during the myriad of “stuck” moments I encountered. LeetCode has a “lite” version with a smaller question bank if the $35 price tag is too steep, as do HackerRank and geeksforgeeks which are other great resources.
What you should do is attempt each question, even if it’s a brute force approach that takes ages to run. Then look at the model solution, and try to figure out what the optimal strategy is. Then read up what the optimal strategy is and try to understand why this is the optimal strategy. Ask yourself questions like “why is Quicksort O(n²) average time complexity?”, why do two pointers and one for loop make more sense than three for loops?

1. Applied Statistics Data science has an implicit dependence on applied statistics, and how implicit that will be depends on the role you’ve applied for. Where do we use applied statistics? It pops up just about anywhere where we need to organise, interpret and derive insights from data.

I studied the following topics intensely during my interviews, and you bet your bottom dollar that I was grilled about each topic:
Descriptive statistics (What distribution does my data follow, what are the modes of the distribution, the expectation, the variance) Probability theory (Given my data follows a Binomial distribution, what is the probability of observing 5 paying customers in 10 click-through events)
Hypothesis testing (forming the basis of any question on A/B testing, T-tests, anova, chi-squared tests, etc).
Regression (Is the relationship between my variables linear, what are potential sources of bias, what are the assumptions behind the ordinary least squares solution)
Bayesian Inference (What are some advantages/disadvantages vs frequentist methods)
If you think this is a lot of material you are not alone, I was massively overwhelmed with the volume of knowledge expected in these kinds of interviews and the plethora of information on the internet that could help me. Two invaluable resources come to mind when I was revising for interviews.
Introduction to Probability and Statistics, an open course on everything listed above including questions and an exam to help you test your knowledge.
Machine Learning: A Bayesian and Optimization Perspective by Sergios Theodoridis. This is more a machine learning text than a specific primer on applied statistics, but the linear algebra approaches outlined here really help drive home the key statistical concepts on regression.
The way you’re going to remember this stuff isn’t through memorisation, you need to solve as many problems as you can get your hands on. Glassdoor is a great repo for the sorts of applied stats questions typically asked in interviews. The most challenging interview I had by far was with G-Research, but I really enjoyed studying for the exam, and their sample exam papers were fantastic resources when it came to testing how far I was getting in my applied statistics revision.

1. Machine Learning Now we come to the beast, the buzzword of our millennial era, and a topic so broad that it can be easy to get so lost in revision that you want to give up. The applied statistics part of this study guide will give you a very very strong foundation to get started with machine learning (which is basically just applied applied statistics written in fancy linear algebra), but there are certain key concepts that came up over and over again during my interviews. Here is a (by no means exhaustive) set of concepts organised by topic:

Metrics — Classification Confusion Matrices, Accuracy, Precision, Recall, Sensitivity F1 Score TPR, TNR, FPR, FNR Type I and Type II errors AUC-ROC Curves
Metrics — Regression Total sum of squares, explained sum of squares, residual sum of squares Coefficient of determination and its adjusted form AIC and BIC Advantages and disadvantages of RMSE, MSE, MAE, MAPE
Bias-Variance Tradeoff, OveUnder-Fitting K Nearest Neighbours algorithm and the choice of k in bias-variance trade-off Random Forests The asymptotic property Curse of dimensionality Model Selection K-Fold Cross Validation L1 and L2 Regularisation Bayesian Optimization
Sampling Dealing with class imbalance when training classification models SMOTE for generating pseudo observations for an underrepresented class Class imbalance in the independent variables Sampling methods Sources of sampling bias Measuring Sampling Error
Hypothesis Testing This really comes under under applied statistics, but I cannot stress enough the importance of learning about statistical power. It’s enormously important in A/B testing.
Regression Models Ordinary Linear Regression, its assumptions, estimator derivation and limitations are covered in significant detail in the sources cited in the applied statistics section. Other regression models you should be familiar with are: Deep Neural Networks for Regression Random Forest Regression XGBoost Regression Time Series Regression (ARIMA/SARIMA) Bayesian Linear Regression Gaussian Process Regression
Clustering Algorithms K-Means Hierarchical Clustering Dirichlet Process Mixture Models
Classification Models Logistic Regression (Most important one, revise well) Multiple Regression XGBoost Classification Support Vector Machines
It’s a lot, but much of the content will be trivial if your applied statistics foundation is strong enough. I would recommend knowing the ins and outs of at least three different classification/regression/clustering methods, because the interviewer could always (and has previously) asked “what other methods could we have used, what are some advantages/disadvantages”? This is a small subset of the machine learning knowledge in the world, but if you know these important examples, the interviews will flow a lot more smoothly.

1. Data Manipulation and Visualisation “What are some of the steps for data wrangling and data cleaning before applying machine learning algorithms”?

We are given a new dataset, the first thing you’ll need to prove is that you can perform an exploratory data analysis (EDA). Before you learn anything realise that there is one path to success in data wrangling: Pandas. The Pandas IDE, when used correctly, is the most powerful tool in a data scientists toolbox. The best way to learn how to use Pandas for data manipulation is to download many, many datasets and learn how to do the following set of tasks as confidently as you making your morning cup of coffee.
One of my interviews involved downloading a dataset, cleaning it, visualising it, performing feature selection, building and evaluating a model all in one hour. It was a crazy hard task, and I felt overwhelmed at times, but I made sure I had practiced building model pipelines for weeks before actually attempting the interview, so I knew I could find my way if I got lost.
Advice: The only way to get good at all this is to practice, and the Kaggle community has an incredible wealth of knowledge on mastering EDAs and model pipeline building. I would check out some of the top ranking notebooks on some of the projects out there. Download some example datasets and build your own notebooks, get familiar with the Pandas syntax.
Data Organisation There are three sure things in life: death, taxes and getting asked to merge datasets, and perform groupby and apply tasks on said merged datasets. Pandas is INCREDIBLY versatile at this, so please practice practice practice.
Data Profiling This involves getting a feel for the “meta” characteristics of the dataset, such as the shape and description of numerical, categorical and date-time features in the data. You should always be seeking to address a set of questions like “how many observations do I have”, “what does the distribution of each feature look like”, “what do the features mean”. This kind of profiling early on can help you reject non-relevant features from the outset, such as categorical features with thousands of levels (names, unique identifiers) and mean less work for you and your machine later on (work smart, not hard, or something woke like that).
Data Visualisation Here you are asking yourself “what does the distribution of my features even look like?”. A word of advice, if you didn’t learn about boxplots in the applied statistics part of the study guide, then here is where I stress you learn about them, because you need to learn how to identify outliers visually and we can discuss how to deal with them later on. Histograms and kernel density estimation plots are extremely useful tools when looking at properties of the distributions of each feature. We can then ask “what does the relationship between my features look like”, in which case Python has a package called seaborn containing very nifty tools like pairplot and a visually satisfying heatmap for correlation plots. Handling Null Values, Syntax Errors and Duplicate Rows/Columns Missing values are a sure thing in any dataset, and arise due to a multitude of different factors, each contributing to bias in their own unique way. There is a whole field of study on how best to deal with missing values (and I once had an interview where I was expected to know individual methods for missing value imputation in much detail). Check out this primer on ways of handling null values.
Syntax errors typically arise when our dataset contains information that has been manually input, such as through a form. This could lead us to erroneously conclude that a categorical feature has many more levels than are actually present, because “Hot”, ‘hOt”, “hot/n” are all considered unique levels. Check out this primer on handling dirty text data. Finally, duplicate columns are of no use to anyone, and having duplicate rows could lead to overrepresentation bias, so it’s worth dealing with them early on.
Standardisation or Normalisation Depending on the dataset you’re working with and the machine learning method you decide to use, it may be useful to standardize or normalize your data so that different scales of different variables don’t negatively impact the performance of your model. There’s a lot here to go through, but honestly it wasn’t as much the “memorise everything” mentality that helped me insofar as it was the confidence building that learning as much as I could instilled in me. I must have failed so many interviews before the formula “clicked” and I realised that all of these things aren’t esoteric concepts that only the elite can master, they’re just tools that you use to build incredible models and derive insights from data.
Best of luck on your job quest guys, if you need any help at all please let me know and I will answer emails/questions when I can.

Hello everyone! This is your run-of-the-mill annual "I'm a new grad, what offer do I take" post with a few extra questions to it. Thanks in advance for your help :).
Some relevant background on me: I'm graduating this December in Math and CS. Most of my background (both work and education) and interest is in Data Science/Machine Learning. I'm originally from the bay area and am generally fond of places with city + nature. I interned at "Company A" (non-FAANG, public bay area tech company) in DS the last two summers and at a smaller company in ML engineering the summer before that.
Now for the offers... I'll quickly note that this is prior to any negotiation:

1. Company A DS return offer: 180k base, 50k RSU per year for 3 years, 22k sign-on, 15k relocation (given as lump sum of cash though). From my internships, I can say the work is highly interesting, culture is laid back, and people are friendly.
2. Uber SWE (bay area): 129k base, 31k equity first year, declining after that, but maybe not because of refreshers, average 13.5k performance bonus, 15k sign-on, 12k relocation. Again, the work sounds fun here, interesting problems and ML opportunities.
3. Indeed DS (in Tokyo!), numbers given with current Yen to USD conversion rate: 73k base, 6k RSU/year, 7-8k performance bonus. The work and culture seem great, comparable to company A. From Glassdoor, this salary seems pretty good for Tokyo tech.
4. I declined a SpaceX SWE offer earlier in the summer, 110k base, 50k stock, 20k sign-on if anyone's interested

Some thoughts on them:
I don't see much of a reason for going to Uber, considering company A's offer seems better to me in pretty much every way, aside from maybe prestige, and even there it's close. As for Indeed Tokyo... damn I would really love to live in Tokyo, and the work/culture are great, too. But giving up ~150k/year seems pretty sad. I'm also not sure if it would be easy to re-enter into the American big tech job market after taking the Indeed position... so yeah, I'm leaning toward Company A right now. A few specific questions though:

1. Do you think it's worth negotiating with any of these? I haven't done any negotiation so far.
2. Any one with experience at Uber or Indeed have thoughts on those companies?
3. How hard would it be to get a FAANG-or-comparable job in the U.S. after working at Indeed Tokyo.

Thanks for the advice!
P.S. On a whim I applied to HRT in late August, made it through second round, and just got rejected ;(. I wouldn't have taken it b/c I don't like finance, but the negotiation power would have been intoxicating.

Let me just explain this crazy situation.
I am an abuse survivor. I was abused by my mother as a child. I ran away from home at 22, and stayed with a relative for awhile, but my mother started to gain access to the relative's home to get to me. I had to leave. Before you tell me that running away at 22 isn't a thing, please put yourself in the shoes of an abuse survivor.
Don't come over here and say "there's no such thing as running away at 22" when you've never been abused. When you're in an abusive situation, with an abusive parent, you ARE running away at 22. When you are literally held hostage with your every move monitored and controlled by a manipulator, you are "running away". This is the very problem I run into when trying to find domestic violence programs for adults. People do not believe adults can be abused, and they don't offer assistance to help these people. People are ignorant about abuse because it isn't happening to them.
I was very much controlled by this parent, and she barred me from having resources. I saved $7,000. She stole all of it. I ran away with nothing, thankful for the kindness of my other relative, but she found a way in there, too. Threatened to kill me and tried to fight me. She would meet me outside. I had to change the time periods when I left the house. Every time I had to call the police before leaving for work. She controlled where I could work by controlling who dropped me off and took me to work. If you've never been in an abusive situation like this, you can't begin to understand how it feels. To add, using manipulative and mental tactics to break my confidence and spirit. I can't imagine you can give advice in this situation.
The place I worked at didn't pay much, and was too far from my new home. I applied for food stamps at this time and was denied because I "made too much". I worked in a state over, which hurt me during tax time. Eventually, I found a job in 2019 in my state that I loved. It was 30 minutes away, but it had a nice environment and I was good at my job. But 2020's pandemic hit, and that job became a nightmare. Didn't work well for my depression or PTSD. They didn't offer good medical insurance either, so I had no doctors to help me work through it. Eventually, the program folded, they moved me to temporary work until I just finally quit after the mental unrest.
I lived off of some retirement money and credit for awhile until I learned of Uber and Door Dash. I relied on Uber and Door Dash to pay my bills. After work one day, I got into a major car crash. A man hit me and ran. They couldn't catch him because the car was stolen. I thought of pressing charges, but it was implied that I had to go to the doctor, and I had no medical insurance. Though my car insurance could reimburse based on the medical expenses, I wasn't going to get much back.
I reached out to my car insurance to see if I would get enough back to replace the car. But after a series of deductibles, I didn't get enough back and my credit was shot. Done for. So, no transportation.
Now, I'm living without transportation. The money I received from my insurance tied me over for three months. In that time frame, I tried to find employment in my local area. Ubers aren't cheap, especially with these inflated prices, and walking in the sweltering heat, I almost passed out several times and got bad sunburn because I can't afford sunblock. Most of the places hiring are at least an hour walk away. I used my last 20.00 on an Uber to go on an interview last week. I'm not landing any jobs. I don't know if my resume is the problem or me. I've tried taking LinkedIn and Glassdoor tips when preparing for interviews. No one will look at resumes for free, so I'm stuck with what's on it.
Now, my home is low on food. I've tried applying for food stamps and health care coverage since March, applying a double application for me and my sibling. First off, back in March the woman I interviewed with was dismissive when I asked her the exact documentation I needed. In order to get food stamps, you have to send in your documentation within 10 business days after the interview. I asked her specifically what I would need. She impatiently told me a list of what I needed would come in the mail. She told me she'd have my Food stamps card expedited so I'd get it sooner.
I waited SEVEN days for the list regarding what I needed to arrive in my mail. That meant I only had three days to gather everything. It cost to take an Uber to the library across town (because my city's library is 3 hours walk from my home). I managed to turn it in the next day, and called in to find out if I had everything. They told me I needed documentation from an account that was closed A YEAR AGO. Because I applied before, they needed that documentation, too. That was connected to Bank of America, which I'd closed years ago. When I called the bank, the told me those closure letters arrive only in the mail and take 7 to 10 business days. Which meant it would arrive passing my due date. I called the Food stamp office about this, expressing my anger, which was why I asked the interviewer to be specific. They managed to press a button and override that document.
I waited for my card. It never arrived. I called about it. Turns out, the woman who I interviewed with processed my documents in the wrong name, under my sibling. They had to update everything. For a few weeks, I had to stretch the little money I had in my account from my Uber drive throughout the month. I couldn't pay bills until my settlement arrived.
When the card arrived, my settlement did, too. So I reported my settlement. Big mistake. I know it's supposed to be done, but these people are not organized. I turned in my documentation before the deadline, called and spoke to someone at my local office. They told me it was sufficient documentation. I asked them ARE YOU SURE because I can't afford to keep sending your documents. They said they were sure. June rolls around, they still don't load my card. I called, they told me to wait. July rolls around and my card is still not loaded.
I call, and this time they tell me it's because I needed documentation for AN ACCOUNT FROM LAST YEAR. Apparently, I'd attempted to apply and interview last year, too, changed my mind when I found out I couldn't afford to, but because it was on record they couldn't process my documents. I asked them why no one called or sent anything in the mail to give me an update, because I SPOKE WITH A SUPERVISOR who told me I wouldn't need anything else. Their attitude on the phone was just "Oh, well, that's what's needed". This meant I had to use money to take an Uber to the library so that I could send this document. Thankfully, this was with a Bank that sends closure letters by email. I finally managed to get it. After 3 to 5 business days, I called to see if it processed.
The person on the phone told me it would take 13 days. I waited 13 days, into August, and called back. THEY STILL HADN'T LOOKED at my documents. I spoke with a supervisor once again. They told me I had all the documents, but here's the clincher: IT WAS NOW TIME FOR AN INTERIM REPORT. By now, I am down to 10 cents and have no money for an Uber, which means I have to walk 2 to 3 hours to the facility. There's no busing, no public transportation, no nothing around my home. And I don't have much food, so I'm walking on no calories.
I tried calling 2-1-1. They were useless. The food pantry options are miles from my home, their meals on wheels are only for people who are elderly or have diagnosed disabilities (which my Psychiatrist won't be available until NOVEMBER to even assess my mental condition), and their other free food options requires you to submit MORE DOCUMENTATION. Which means spend money to get to the library, spend money to print and scan and fax at the library, and spend money to actually pick up the food at their useless pantries. There are very few delivery options for just POOR people. They couldn't give me any good transportation options that helped dirt poor people.
They suggested a Dial-a-ride, but Dial-a-ride mislead the public with false advertising on their website, saying you only have to make an appointment 24 hours ahead of time. I call them, and they tell me you have to put in 2 weeks in advance. A lot of good that does me.
The local Housing Authority has been helpful. I applied to them in MARCH and they finally approved my documentation in AUGUST to help with my rent. Though that's a huge delay, it has come at the perfect time. My landlord still hasn't gotten the money though, so I hope it works out. I called them, and they told me it should. Crossing fingers it will help with my rent.
Now, my issue is with trying to get utilities paid until I can find local employment. I have to deal with the same people who run Dial-a-ride, and I get the feeling I'll need MORE DOCUMENTATION just to get my utilities covered.
To wrap this all up, I was wondering if anybody knows how I can get food in my home, a place to get my utilities paid, a good place to call for help with unemployment, and some transportation. I'm at my wit's end. I'm literally on my last leg. This is my last hope. To anyone who can help me, your kindness is appreciated and I will never forget it.

Let me just explain this crazy situation.
I am an abuse survivor. I was abused by my mother as a child. I finally found the courage to run away from home at 22, despite the crazy controlling methods my mother had, with no money and stayed with a relative for awhile, but my mother started to gain access to the relative's home to get to me. I had to leave there, too, with little money.
The place I worked at didn't pay much, and was too far from my new home. I applied for food stamps at this time and was denied because I "made too much". I worked in a state over, which hurt me during tax time. Eventually, I found a job in 2019 in my state that I loved. It was 30 minutes away, but it had a nice environment and I was good at my job. But 2020's pandemic hit, and that job became a nightmare. Didn't work well for my depression or PTSD. They didn't offer good medical insurance either, so I had no doctors to help me work through it. Eventually, the program folded, they moved me to temporary work until I just finally quit after the mental unrest.
I lived off of some retirement money and credit for awhile until I learned of Uber and Door Dash. I relied on Uber and Door Dash to pay my bills. After work one day, I got into a major car crash. A man hit me and ran. They couldn't catch him because the car was stolen. I thought of pressing charges, but it was implied that I had to go to the doctor, and I had no medical insurance. Though my car insurance could reimburse based on the medical expenses, I wasn't going to get much back.
I reached out to my car insurance to see if I would get enough back to replace the car. But after a series of deductibles, I didn't get enough back and my credit was shot. Done for. So, no transportation.
Now, I'm living without transportation. The money I received from my insurance tied me over for three months. In that time frame, I tried to find employment in my local area. Ubers aren't cheap, especially with these inflated prices, and walking in the sweltering heat, I almost passed out several times and got bad sunburn because I can't afford sunblock. Most of the places hiring are at least an hour walk away. I used my last 20.00 on an Uber to go on an interview last week. I'm not landing any jobs. I don't know if my resume is the problem or me. I've tried taking LinkedIn and Glassdoor tips when preparing for interviews. No one will look at resumes for free, so I'm stuck with what's on it.
Now, my home is low on food. I've tried applying for food stamps and health care coverage since March, applying a double application for me and my sibling. First off, back in March the woman I interviewed with was dismissive when I asked her the exact documentation I needed. In order to get food stamps, you have to send in your documentation within 10 business days after the interview. I asked her specifically what I would need. She impatiently told me a list of what I needed would come in the mail. She told me she'd have my Food stamps card expedited so I'd get it sooner.
I waited SEVEN days for the list regarding what I needed to arrive in my mail. That meant I only had three days to gather everything. It cost to take an Uber to the library across town (because my city's library is 3 hours walk from my home). I managed to turn it in the next day, and called in to find out if I had everything. They told me I needed documentation from an account that was closed A YEAR AGO. Because I applied before, they needed that documentation, too. That was connected to Bank of America, which I'd closed years ago. When I called the bank, the told me those closure letters arrive only in the mail and take 7 to 10 business days. Which meant it would arrive passing my due date. I called the Food stamp office about this, expressing my anger, which was why I asked the interviewer to be specific. They managed to press a button and override that document.
I waited for my card. It never arrived. I called about it. Turns out, the woman who I interviewed with processed my documents in the wrong name, under my sibling. They had to update everything. For a few weeks, I had to stretch the little money I had in my account from my Uber drive throughout the month. I couldn't pay bills until my settlement arrived.
When the card arrived, my settlement did, too. So I reported my settlement. Big mistake. I know it's supposed to be done, but these people are not organized. I turned in my documentation before the deadline, called and spoke to someone at my local office. They told me it was sufficient documentation. I asked them ARE YOU SURE because I can't afford to keep sending your documents. They said they were sure. June rolls around, they still don't load my card. I called, they told me to wait. July rolls around and my card is still not loaded.
I call, and this time they tell me it's because I needed documentation for AN ACCOUNT FROM LAST YEAR. Apparently, I'd attempted to apply and interview last year, too, changed my mind when I found out I couldn't afford to, but because it was on record they couldn't process my documents. I asked them why no one called or sent anything in the mail to give me an update, because I SPOKE WITH A SUPERVISOR who told me I wouldn't need anything else. Their attitude on the phone was just "Oh, well, that's what's needed". This meant I had to use money to take an Uber to the library so that I could send this document. Thankfully, this was with a Bank that sends closure letters by email. I finally managed to get it. After 3 to 5 business days, I called to see if it processed.
The person on the phone told me it would take 13 days. I waited 13 days, into August, and called back. THEY STILL HADN'T LOOKED at my documents. I spoke with a supervisor once again. They told me I had all the documents, but here's the clincher: IT WAS NOW TIME FOR AN INTERIM REPORT. By now, I am down to 10 cents and have no money for an Uber, which means I have to walk 2 to 3 hours to the facility. There's no busing, no public transportation, no nothing around my home. And I don't have much food, so I'm walking on no calories.
I tried calling 2-1-1. They were useless. The food pantry options are miles from my home, their meals on wheels are only for people who are elderly or have diagnosed disabilities (which my Psychiatrist won't be available until NOVEMBER to even assess my mental condition), and their other free food options requires you to submit MORE DOCUMENTATION. Which means spend money to get to the library, spend money to print and scan and fax at the library, and spend money to actually pick up the food at their useless pantries. There are very few delivery options for just POOR people. They couldn't give me any good transportation options that helped dirt poor people.
They suggested a Dial-a-ride, but Dial-a-ride mislead the public with false advertising on their website, saying you only have to make an appointment 24 hours ahead of time. I call them, and they tell me you have to put in 2 weeks in advance. A lot of good that does me.
The Indiana Housing Authority has been helpful. I applied to them in MARCH and they finally approved my documentation in AUGUST to help with my rent. Though that's a huge delay, it has come at the perfect time. My landlord still hasn't gotten the money though, so I hope it works out. I called them, and they told me it should. Crossing fingers it will help with my rent.
Now, my issue is with trying to get utilities paid until I can find local employment. I have to deal with the same people who run Dial-a-ride, and I get the feeling I'll need MORE DOCUMENTATION just to get my utilities covered.
To wrap this all up, I was wondering if anybody knows how I can get food in my home, a place to get my utilities paid, a good place to call for help with unemployment, and some transportation. I'm at my wit's end. I'm literally on my last leg. This is my last hope. To anyone who can help me, your kindness is appreciated and I will never forget it.

Let me just explain this crazy situation.
I am an abuse survivor. I was abused by my mother as a child. I ran away from home at 22, and stayed with a relative for awhile, but my mother started to gain access to the relative's home to get to me. I had to leave.
The place I worked at didn't pay much, and was too far from my new home. I applied for food stamps at this time and was denied because I "made too much". I worked in a state over, which hurt me during tax time. Eventually, I found a job in 2019 in my state that I loved. It was 30 minutes away, but it had a nice environment and I was good at my job. But 2020's pandemic hit, and that job became a nightmare. Didn't work well for my depression or PTSD. They didn't offer good medical insurance either, so I had no doctors to help me work through it. Eventually, the program folded, they moved me to temporary work until I just finally quit after the mental unrest.
I lived off of some retirement money and credit for awhile until I learned of Uber and Door Dash. I relied on Uber and Door Dash to pay my bills. After work one day, I got into a major car crash. A man hit me and ran. They couldn't catch him because the car was stolen. I thought of pressing charges, but it was implied that I had to go to the doctor, and I had no medical insurance. Though my car insurance could reimburse based on the medical expenses, I wasn't going to get much back.
I reached out to my car insurance to see if I would get enough back to replace the car. But after a series of deductibles, I didn't get enough back and my credit was shot. Done for. So, no transportation.
Now, I'm living without transportation. The money I received from my insurance tied me over for three months. In that time frame, I tried to find employment in my local area. Ubers aren't cheap, especially with these inflated prices, and walking in the sweltering heat, I almost passed out several times and got bad sunburn because I can't afford sunblock. Most of the places hiring are at least an hour walk away. I used my last 20.00 on an Uber to go on an interview last week. I'm not landing any jobs. I don't know if my resume is the problem or me. I've tried taking LinkedIn and Glassdoor tips when preparing for interviews. No one will look at resumes for free, so I'm stuck with what's on it.
Now, my home is low on food. I've tried applying for food stamps and health care coverage since March, applying a double application for me and my sibling. First off, back in March the woman I interviewed with was dismissive when I asked her the exact documentation I needed. In order to get food stamps, you have to send in your documentation within 10 business days after the interview. I asked her specifically what I would need. She impatiently told me a list of what I needed would come in the mail. She told me she'd have my Food stamps card expedited so I'd get it sooner.
I waited SEVEN days for the list regarding what I needed to arrive in my mail. That meant I only had three days to gather everything. It cost to take an Uber to the library across town (because my city's library is 3 hours walk from my home). I managed to turn it in the next day, and called in to find out if I had everything. They told me I needed documentation from an account that was closed A YEAR AGO. Because I applied before, they needed that documentation, too. That was connected to Bank of America, which I'd closed years ago. When I called the bank, the told me those closure letters arrive only in the mail and take 7 to 10 business days. Which meant it would arrive passing my due date. I called the Food stamp office about this, expressing my anger, which was why I asked the interviewer to be specific. They managed to press a button and override that document.
I waited for my card. It never arrived. I called about it. Turns out, the woman who I interviewed with processed my documents in the wrong name, under my sibling. They had to update everything. For a few weeks, I had to stretch the little money I had in my account from my Uber drive throughout the month. I couldn't pay bills until my settlement arrived.
When the card arrived, my settlement did, too. So I reported my settlement. Big mistake. I know it's supposed to be done, but these people are not organized. I turned in my documentation before the deadline, called and spoke to someone at my local office. They told me it was sufficient documentation. I asked them ARE YOU SURE because I can't afford to keep sending your documents. They said they were sure. June rolls around, they still don't load my card. I called, they told me to wait. July rolls around and my card is still not loaded.
I call, and this time they tell me it's because I needed documentation for AN ACCOUNT FROM LAST YEAR. Apparently, I'd attempted to apply and interview last year, too, changed my mind when I found out I couldn't afford to, but because it was on record they couldn't process my documents. I asked them why no one called or sent anything in the mail to give me an update, because I SPOKE WITH A SUPERVISOR who told me I wouldn't need anything else. Their attitude on the phone was just "Oh, well, that's what's needed". This meant I had to use money to take an Uber to the library so that I could send this document. Thankfully, this was with a Bank that sends closure letters by email. I finally managed to get it. After 3 to 5 business days, I called to see if it processed.
The person on the phone told me it would take 13 days. I waited 13 days, into August, and called back. THEY STILL HADN'T LOOKED at my documents. I spoke with a supervisor once again. They told me I had all the documents, but here's the clincher: IT WAS NOW TIME FOR AN INTERIM REPORT. By now, I am down to 10 cents and have no money for an Uber, which means I have to walk 2 to 3 hours to the facility. There's no busing, no public transportation, no nothing around my home. And I don't have much food, so I'm walking on no calories.
I tried calling 2-1-1. They were useless. The food pantry options are miles from my home, their meals on wheels are only for people who are elderly or have diagnosed disabilities (which my Psychiatrist won't be available until NOVEMBER to even assess my mental condition), and their other free food options requires you to submit MORE DOCUMENTATION. Which means spend money to get to the library, spend money to print and scan and fax at the library, and spend money to actually pick up the food at their useless pantries. There are very few delivery options for just POOR people. They couldn't give me any good transportation options that helped dirt poor people.
They suggested a Dial-a-ride, but Dial-a-ride mislead the public with false advertising on their website, saying you only have to make an appointment 24 hours ahead of time. I call them, and they tell me you have to put in 2 weeks in advance. A lot of good that does me.
The Indiana Housing Authority has been helpful. I applied to them in MARCH and they finally approved my documentation in AUGUST to help with my rent. Though that's a huge delay, it has come at the perfect time. My landlord still hasn't gotten the money though, so I hope it works out. I called them, and they told me it should. Crossing fingers it will help with my rent.
Now, my issue is with trying to get utilities paid until I can find local employment. I have to deal with the same people who run Dial-a-ride, and I get the feeling I'll need MORE DOCUMENTATION just to get my utilities covered.
To wrap this all up, I was wondering if anybody knows how I can get food in my home, a place to get my utilities paid, a good place to call for help with unemployment, and some transportation. I'm at my wit's end. I'm literally on my last leg. This is my last hope. To anyone who can help me, your kindness is appreciated and I will never forget it.

Let me just explain this crazy situation.
I am an abuse survivor. I was abused by my mother as a child. I ran away from home at 22, and stayed with a relative for awhile, but my mother started to gain access to the relative's home to get to me. I had to leave.
Don't come over here and say "there's no such thing as running away at 22" when you've never been abused. When you're in an abusive situation, with an abusive parent, you ARE running away at 22. This is the very problem I run into when trying to find domestic violence programs for adults. People do not believe adults can be abused, and they don't offer assistance to help these people. People are ignorant about abuse because it isn't happening to them.
I was very much controlled by this parent, and she barred me from having resources. I saved $7,000. She stole all of it. I ran away with nothing, thankful for the kindness of my other relative, but she found a way in there, too. Threatened to kill me and tried to fight me. She would meet me outside. I had to change the time periods when I left the house. Every time I had to call the police before leaving for work. She controlled where I could work by controlling who dropped me off and took me to work. If you've never been in an abusive situation like this, you can't begin to understand how it feels. To add, using manipulative and mental tactics to break my confidence and spirit. I can't imagine you can give advice in this situation.
The place I worked at didn't pay much, and was too far from my new home. I applied for food stamps at this time and was denied because I "made too much". I worked in a state over, which hurt me during tax time. Eventually, I found a job in 2019 in my state that I loved. It was 30 minutes away, but it had a nice environment and I was good at my job. But 2020's pandemic hit, and that job became a nightmare. Didn't work well for my depression or PTSD. They didn't offer good medical insurance either, so I had no doctors to help me work through it. Eventually, the program folded, they moved me to temporary work until I just finally quit after the mental unrest.
I lived off of some retirement money and credit for awhile until I learned of Uber and Door Dash. I relied on Uber and Door Dash to pay my bills. After work one day, I got into a major car crash. A man hit me and ran. They couldn't catch him because the car was stolen. I thought of pressing charges, but it was implied that I had to go to the doctor, and I had no medical insurance. Though my car insurance could reimburse based on the medical expenses, I wasn't going to get much back.
I reached out to my car insurance to see if I would get enough back to replace the car. But after a series of deductibles, I didn't get enough back and my credit was shot. Done for. So, no transportation.
Now, I'm living without transportation. The money I received from my insurance tied me over for three months. In that time frame, I tried to find employment in my local area. Ubers aren't cheap, especially with these inflated prices, and walking in the sweltering heat, I almost passed out several times and got bad sunburn because I can't afford sunblock. Most of the places hiring are at least an hour walk away. I used my last 20.00 on an Uber to go on an interview last week. I'm not landing any jobs. I don't know if my resume is the problem or me. I've tried taking LinkedIn and Glassdoor tips when preparing for interviews. No one will look at resumes for free, so I'm stuck with what's on it.
Now, my home is low on food. I've tried applying for food stamps and health care coverage since March, applying a double application for me and my sibling. First off, back in March the woman I interviewed with was dismissive when I asked her the exact documentation I needed. In order to get food stamps, you have to send in your documentation within 10 business days after the interview. I asked her specifically what I would need. She impatiently told me a list of what I needed would come in the mail. She told me she'd have my Food stamps card expedited so I'd get it sooner.
I waited SEVEN days for the list regarding what I needed to arrive in my mail. That meant I only had three days to gather everything. It cost to take an Uber to the library across town (because my city's library is 3 hours walk from my home). I managed to turn it in the next day, and called in to find out if I had everything. They told me I needed documentation from an account that was closed A YEAR AGO. Because I applied before, they needed that documentation, too. That was connected to Bank of America, which I'd closed years ago. When I called the bank, the told me those closure letters arrive only in the mail and take 7 to 10 business days. Which meant it would arrive passing my due date. I called the Food stamp office about this, expressing my anger, which was why I asked the interviewer to be specific. They managed to press a button and override that document.
I waited for my card. It never arrived. I called about it. Turns out, the woman who I interviewed with processed my documents in the wrong name, under my sibling. They had to update everything. For a few weeks, I had to stretch the little money I had in my account from my Uber drive throughout the month. I couldn't pay bills until my settlement arrived.
When the card arrived, my settlement did, too. So I reported my settlement. Big mistake. I know it's supposed to be done, but these people are not organized. I turned in my documentation before the deadline, called and spoke to someone at my local office. They told me it was sufficient documentation. I asked them ARE YOU SURE because I can't afford to keep sending your documents. They said they were sure. June rolls around, they still don't load my card. I called, they told me to wait. July rolls around and my card is still not loaded.
I call, and this time they tell me it's because I needed documentation for AN ACCOUNT FROM LAST YEAR. Apparently, I'd attempted to apply and interview last year, too, changed my mind when I found out I couldn't afford to, but because it was on record they couldn't process my documents. I asked them why no one called or sent anything in the mail to give me an update, because I SPOKE WITH A SUPERVISOR who told me I wouldn't need anything else. Their attitude on the phone was just "Oh, well, that's what's needed". This meant I had to use money to take an Uber to the library so that I could send this document. Thankfully, this was with a Bank that sends closure letters by email. I finally managed to get it. After 3 to 5 business days, I called to see if it processed.
The person on the phone told me it would take 13 days. I waited 13 days, into August, and called back. THEY STILL HADN'T LOOKED at my documents. I spoke with a supervisor once again. They told me I had all the documents, but here's the clincher: IT WAS NOW TIME FOR AN INTERIM REPORT. By now, I am down to 10 cents and have no money for an Uber, which means I have to walk 2 to 3 hours to the facility. There's no busing, no public transportation, no nothing around my home. And I don't have much food, so I'm walking on no calories.
I tried calling 2-1-1. They were useless. The food pantry options are miles from my home, their meals on wheels are only for people who are elderly or have diagnosed disabilities (which my Psychiatrist won't be available until NOVEMBER to even assess my mental condition), and their other free food options requires you to submit MORE DOCUMENTATION. Which means spend money to get to the library, spend money to print and scan and fax at the library, and spend money to actually pick up the food at their useless pantries. There are very few delivery options for just POOR people. They couldn't give me any good transportation options that helped dirt poor people.
They suggested a Dial-a-ride, but Dial-a-ride mislead the public with false advertising on their website, saying you only have to make an appointment 24 hours ahead of time. I call them, and they tell me you have to put in 2 weeks in advance. A lot of good that does me.
The local Housing Authority has been helpful. I applied to them in MARCH and they finally approved my documentation in AUGUST to help with my rent. Though that's a huge delay, it has come at the perfect time. My landlord still hasn't gotten the money though, so I hope it works out. I called them, and they told me it should. Crossing fingers it will help with my rent.
Now, my issue is with trying to get utilities paid until I can find local employment. I have to deal with the same people who run Dial-a-ride, and I get the feeling I'll need MORE DOCUMENTATION just to get my utilities covered.
To wrap this all up, I was wondering if anybody knows how I can get food in my home, a place to get my utilities paid, a good place to call for help with unemployment, and some transportation. I'm at my wit's end. I'm literally on my last leg. This is my last hope. To anyone who can help me, your kindness is appreciated and I will never forget it.

This article is a comprehensive guide that covers popular hiring platforms, average salaries of Go developers worldwide, and various employment types. By the end of this lengthy read, you will have everything you need to know before hiring a Golang developer.

How does the popularity of the Go language affect the hiring process?

Knowing Go has become a trump card for developers who have also gained experience with other programming languages such as Java, Ruby, Python, or Javascript. According to the Stack Overflow 2021 Developer Survey, Go, also known as Golang, is the fourth most popular programming language.
Hiring developers familiar with both popular and niche technologies is becoming increasingly difficult as the demand for software engineers grows. According to many reports, developers who work with niche programming languages like Rust, Go, and Scala are more likely to earn higher average salaries than their more common counterparts, owing to their scarcity.

What distinguishes Go from other programming languages?

Golang is widely used in data science and artificial intelligence applications. Both are seeing increased investment from startups and companies undergoing digital transformation. As a result, more companies are looking for candidates with strong analytical skills and a solid understanding of data.
Golang is an open-source programming language created by Google in 2007 that combines the performance and security benefits of a compiled language like C++ with the speed of a dynamic language like Python. Go was designed to run on multiple cores. Its concurrency feature allows it to handle multiple requests simultaneously while maintaining high performance. Google wants its servers to be as fast as possible, so they created Go to meet that need. The faster the code can execute—the faster internet TCP or UDP over IP requests can be received, processed, and returned to the client—the more performant and scalable Go becomes.
Furthermore, the Golang programming language has an excellent standard library, allowing you to create web apps without a framework. Its standard library is also useful for DevOps engineers. It includes file processing, HTTP web services, JSON processing, native concurrency and parallelism support, and built-in testing modules.
Uber’s microservice, which implements dynamic pricing in neighborhoods where many people request rides simultaneously and shows users which products are available at a given location, was notable for its use of Go programming.

What is the global average salary for Golang developers?

On Glassdoor, we’ve compiled data on the average salaries of Go developers. Please keep in mind that the platform considers the earnings of developers with varying levels of expertise, so actual salaries may vary from case to case. Furthermore, a backend developer who does not speak English and works on a local project will earn significantly less than a programmer who works for an outsourcing company.
Nonetheless, this study demonstrates how incomes differ across countries, which is caused, at the very least, by differences in living costs and taxation levels.

Go software engineer salaries according to Glassdoor

These figures represent the median earnings reported by Glassdoor’s proprietary Total Pay Estimate model, based on salaries submitted by platform users. Wages in India, the United States, Canada, Mexico, and the United Kingdom include a base salary and additional pay such as a cash bonus, commission, tips, and profit sharing.
According to Glassdoor, the highest-paid Go developers work in North America and Western Europe. Engineers from India, on the other hand, are the least expensive.
CountrySalary per year, USDUnited States$142,000Canada$86,000Mexico$59,000Brazil$82,000United Kingdom$83,000Germany$69,000Romania$56,000Bulgaria$47,000Ukraine$44,000China$70,000India$17,000Australia$82,000
Many companies in countries such as the United States or Western Europe prefer to hire remotely using innovative models such as staff augmentation. Thus, hiring contractors from other countries may be the solution if you want to hire a professional Go developer but are limited in tech talent. Furthermore, this solution is cost-effective because you will not have to pay for office rental, equipment, or bonuses—you only pay for the services. Now that we’ve looked at the average salaries of Go developers worldwide let’s look at how you can use this information before hiring a Golang developer.

Hiring a Golang Developer: Geographical Options

If you want to hire a Go developer, you have three options based on location. You can hire a local engineer, a nearshore developer, or an offshore developer (or development team).

Recruiting local talent

When hiring local talent, developers typically work in the same office with a team. Even if they work remotely or in a hybrid work model, they are all in the same time zone, so team members can quickly call or meet to discuss project details.
Traditional hiring will work for this method; start by searching online job boards like Angel.co or Glassdoor.com. You can also hire developers by organizing or participating in local events such as hackathons and tech conferences. There have been fewer in-person events in recent years, as many have moved online. Finally, you can approach headhunting firms for an in-house backend or full stack developer, or you can look in your local market using your HR services.

Hiring nearshore and offshore developers

Nearshore and offshore outsourcing provide access to a larger pool of developers, preventing a talent shortage.
In both of these cases, the hiring process is very similar. You should first look for individuals and organizations with high ratings. Ratings can be found on B2B platforms such as Clutch and GoodFirms before hiring a Golang developer or development company. Companies may hire web developers for nearshore positions through regional events (tech conferences and hackathons).

Four Models for Hiring a Golang Developer

Several hiring models are available, including in-house hiring, staff augmentation, freelance, and outsourcing software development.

In-house Hiring

You must pay a monthly salary plus benefits if you hire an in-house developer (financial and non-financial). Because they are committed to developing the product and the company, in-house developers are the most engaged—they delve into the product details and come up with the best solutions. As a result, at the core development stage, in-house recruitment is the best solution.
On the other hand, this method is more expensive because employers are required to pay for health insurance and make retirement contributions. Furthermore, the hiring process may take much longer because of the additional onboarding requirements for in-house employees.

Staff Augmentation

Staff augmentation is a solution for businesses that want to rapidly scale their development process by hiring a Golang developer who are only focused on one project. You will directly manage full-time employed programmers at software development agencies. You will be able to communicate with each of them.
Staff augmentation is just as safe as in-house hiring, but it happens much faster. By using the YouTeam online platform, for example, you will be dealing with a trusted network of developers from Eastern Europe and Latin America who are available for immediate hire. It takes 48 hours to receive a shortlist of Go engineers who meet your specifications.
Team augmentation, like in-house options, necessitates managers’ attention during onboarding. You must align the workflow and establish communication between the in-house and remote teams.
Read more: In-House Recruitment vs. IT Staff Augmentation

Outsourcing

The process is fairly straightforward if your company decides to hire through an outsourcing service. First, contact a Go development shop and agree on the project requirements. Then, a remote development team will work on your project.
Tech companies use this business practice to focus on the core aspects of the business, assigning app development to outside organizations managed by the CTO or product owner of the in-house team. Outsourcing, on the other hand, limits communication between the company and external providers and may pose security risks because sensitive data is accessible to multiple parties.
Read more: Staff Augmentation vs IT Project Outsourcing: Pros, Cons & Differences

Freelancing

Hiring freelancers is appropriate for short-term projects, small tasks, and businesses with limited resources. Suppose your company decides to hire a freelance Go developer through a platform like Upwork. In that case, you must pay the platform the hourly rate plus a commission. Because freelancers must pay a commission, their hourly rates may be higher.
Even though freelancers are the quickest to hire, this hiring model is fraught with project delays and cancellations. Unlike dedicated development teams and contractors, freelancers are responsible for multiple jobs, and the quality of their output may fall short of the client’s expectations. You do not have the same level of control over a freelancer that you do over an employee.

Where to Find And Hire Go Developers?

Depending on the hiring model, we recommend a list of Go developer groups, job boards, directories, and communities. These links will direct you to communities where you can post Golang developer jobs, find contractors, or connect directly with the most active users.

Staff augmentation

• Companies that provide IT Staff Augmentation services are the best choice for this model, such as Bestarion.

Outsourcing

• Clutch recommends development firms.
• GoodFirms has Golang development companies.

Freelancing

• Create a job listing on Upwork.
• Hubstaff talent can help you find remote Golang engineers.

In-house Development: Job-boards

• Glassdoor for employers
• Indeed for employers

Communities and groups

• Go official Twitter account
• Go at GitHub
• Gophers Slack community (gopher is an iconic mascot of the Go project)
• Local meetup groups for Go developers

Comparing Go engineers from the United States, Europe, and Asia

American developers are frequently hired long-term by product companies, with the possibility of additional training.
Developers with experience in software development firms (more prevalent in Europe and Asia) typically know 1-2 focus languages in which they have deep expertise and years of experience. That is why contractors from these world regions are so valuable — such experts can add the most value to a project.
When European developers focus on hard skills, Americans will be the best at soft skills, and this difference will be even more pronounced in Asia. This disparity is due to cultural differences and different types of businesses and roles. First and foremost, as a contractor, you are expected to produce results.
In general, a country’s average income has nothing to do with the qualifications of its workforce. Ukraine, with 300,000 high-quality tech specialists, has a reputation as a reliable IT outsourcing destination due to a cultural fit with EU and US customers, as we all share the same values.
Examine the spreadsheet for a comparison of developers from the United States, Ukraine, and India in terms of time zone convenience and English language proficiency:
Go DeveloperUnited StatesEuropeAsiaAverage Salary$142K$54K$27KTime Zone ConveniencePerfect for the US and Europe.Perfect for Western European countries and the US.Time differences between European countries and the US.English ProficiencyNativeIntermediate to HighElementary to High

What Should You Ask Go Engineers in an Interview?

Make sure you have a standardized interviewing process to evaluate candidates better. Make a list of the most important questions you want to cover and write down potential answers. Whatever employment type you choose, there are two main categories of questions you should ask a Go engineer in real-time:
Hard skills: Depending on the tasks at hand, you should focus on the following areas of knowledge:

• Understanding of common Goroutine and channel patterns
• Knowledge of Go frameworks and tools, such as:
• Go’s templating language
• Code generation tools, such as Stringer
• Dependency management tools such as Godep, Sltr
• Knowledge of code versioning tools such as Git, SVN, and Mercurial is required.
• Capability to write effective and clean Godoc comments

More examples of questions for hard-skills interviews with Go developers (with answers) can be found here.
Soft skills: After assessing an interviewee’s abilities, you should modify the conversation to confirm their cultural fit and background. This way, you can demonstrate that the candidate is a great team player who shares your company’s values.

Why Should You Hire Your Next Go Developer from Bestarion?

Bestarion is an outsourcing company in Asia that helps hire a top Golang developer through an IT staff augmentation service. And this is why:

• We have pre-interviewed our pool of middle and senior Golang developers to ensure that they are the best fit to meet the needs of our customers.
• It takes a short time to receive a verified list of candidates after contacting Bestarion.
• No legal burden. Our experts will help you communicate with project engineers and answer any legal or financial questions you may have.

Please [contact us](mailto:%[email protected]) if you have any questions or ideas or want to learn more about staff augmentation.