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Ask HN: I realise data science is not for me and feel depressed
146 points by boa00 5 months ago | hide | past | favorite | 140 comments
I am a fourth year student in Eastern Europe, studying Math and Economics. This is the final year, and I have 3-4 months till graduation. At the same time, I've been working full time as a Data Scientist at a big telecom company for the last several months. And I think it's not for me

The project here is interesting, but I realize that I do not like any of the "real" DS tasks, e.g. anything that involves actually building a model from the statistical standpoint. Now, I write a lot of SQL: the company has hundreds of billions of calling records, so you have to really think about the queries you write, and even if they are quite optimized I still sit here for a long time waiting for the response. And even that is more exciting than any of the statistical tasks I face

Little background: I started coding when I was 16, back then I built an iOS app using Swift to help me learn English vocabulary. After that, I've been coding as a hobby on the side during my studies. I liked mathematics and statistics as a freshman, and during my second year found out about Data Science. Given my background, I thought it would be a perfect fit for me. I built a few pet-projects using ML during my third year, and started applying. They impressed one of the employers (big bank), so these projects basically landed me my first internship, which led me to the current job

The thing I like the most is actually building stuff with my hands, and I think SWE is a better fit here. I guess this is the reason I never liked Kaggle. Also, most of my internship I spent building a simple web interface for the existing model (mostly back, like connecting to DB, transforming data, deploying to Linux, etc), which was 100% SWE task and I liked it. So there were hints along the way...

How would you recommend me to switch to SWE the fastest way possible?

I'm quite depressed now because I've put enormous effort into switching to DS: I applied to 80 job postings before I got my first internship, and I feel this is for nothing now. Also, my university and faculty considered to be really difficult, so studying DS on the side was brutal.

Besides, I live in Russia and want to relocate (for obv reasons), and feel like it's easier with SWE skills (especially given that I know English and in the process of receiving EU passport). This puts an enormous time pressure on me given how the things are playing out now...

I would appreciate any opinion/advice!




Firstly, finish your degree.

For most employers, just checking off the degree is more important than exactly what it is. This is especially true for software engineering. You will have many, many coworkers who have degrees in physics or bioinformatics or mathematics and work as SWEs. Most of their stories will be exactly the same as yours, although "...but there weren't any good paying jobs so..." will be in the running.


To OP:

Good advice.

Listen to this.

Focus on finishing the degree, and if possible, get as good grades as possible.

That will open a lot of doors.

____

To this comment:

I have switched from Physics to Deep Learning. This is more because of "getting to know myself better" than money.

I grew up being good at math (scorewise when little, and later, actually getting and understanding) and science. And I had a lot of biographies and a-little-harder-than pop-sci kind of science articles at home. I thought that I would become a Physicist and become a Professor.

College was a big disappointed. The beaurocracy aside, the college system relies on memorizing numerical problems, proofs, and regurgitating them during test.

And also, the field of Physics is highly saturated. It feels like all the stuff has been done. Need a field where I can contribute, rather than just watch passively.

In college, for the first time, I got to work in a real Electronics lab in my Physics major class. Absolutely loved the experience.

Reading theory by bigshots in books, and applying them with my own hands! Building stuff! That's when I first found out I loved building things and applying things on my own hand rather as much as, or more than I loved the ivory tower of pure theory.

Coupled with my frustration, I decided I will become a programmer because that is where I got to build things and not just regurgitate text.

My metor-friends (older) told me that Data Science was hot. Better get into that. Although they meant analysis type work, I soon transitioned to Deep Learning. Vision particularly.

I am on brink of publishing two research papers independently, and worked in two jobs where I developed Deep Learning systems.

I am very happy that I gave up Physics.

I may not even stay here. This transition has taught me to be less stringent on life's choices.

I have also learned that I don't particularly like Physics or Math or Deep Learning. I like esoteric things that not many can do, pay well, give intellectual kicks, opportunity to work with hands, and are math-y.


Agree except possibly the 'good grades' part. I'm self-taught and work at a FAANG. I'm also a technical interviewer. I have never once asked for or looked at a candidate's GPA.

Looking at someone's GPA honestly wouldn't help me much at all. It's not like I know how rigorous <insert university here>'s math or economics departments are.

Unless you went to a college that's a household name in your geographical region (for example, Harvard in the United States), I'd leave off the GPA from the resume.

Try to learn as much as you can, but don't fret about getting the best grades. Very few people will honestly care about your grades; they care that you graduated and whether you have the technical and interpersonal skills to fit on the team. If a person won't hire you because your don't have a 4.0, trust me that's not someone you want to work for in the long run.


Totally agree. I do a lot of interviews for my employer and no one cares about your GPA or really even your degree once you have some work experience.

I've been working in IT and software development since I left high school; it was never a barrier that I went to school to be an aircraft mechanic and don't have a tech-related degree.


Hmm, re-reading your post and thinking more about the specifics, I think the next steps vary a lot depending on your personal experience and resources.

You can basically break a "software engineering" degree down to three components - writing code, "core theory", and "specialist knowledge".

You may already have "writing code" down well enough for entry level gigs; if not, side projects are a fine way to get you there. Look over job postings that interest you, see what languages they ask for, try writing some code in that language.

For "core theory", there are three basic classes you'd ordinarily take: algorithms/data structures, an introduction to compilers, and an introduction to operating systems.

If you've taken these courses already while in your current degree program, great, you're done. Don't worry about all of the extra specialist knowledge, you can pick it up later if you need or want it. You'll know as much as any other entry level generic software engineer.

Algorithms/data structures tells you why some code is fast and why some is slow, and the theory of fast code. Compilers teaches you how programs work under the hood, how the computer actually interprets and executes your programs. Operating systems teach you how the computer as a whole works what happens when you write to a file or a socket or a screen.

You don't need to be able to write a compiler or am operating system from scratch to be a good generic software engineer, but having a rough overview of how the entire system works is one of the things that elevates you past being "just" a self-taught coder. It helps you understand what your code is doing as well as how to write it.

If you haven't been exposed to the "core theory", you're probably best off just trying to pick up books or (free) online courses on the subject. Unless you have just fantastic financial resources you shouldn't try to change your degree or get extra formal schooling in the subject. As long as you can write code, there will be people happy to hire you as a SWE, so you don't even have to wait to master the core theory to start applying to jobs.

Start with algorithms/data structures. It's the most useful and a good opportunity to get more practice writing code in, especially in new languages.


For a basic intro to compilers/OS I'd recommend the Nand2Tetris course.

It's the best course I've ever done tbh, and is actually interesting. I never felt like I was forcing my way through it.


Thank you for this amazing comment. It has helped me reorganize my understanding of the relationship between computer science and software engineering.


> algorithms/data structures

Certainly someone can recommend a good resource here?

The Wizard Book maybe?


Agreed. Speaking as someone who has hired hundreds of software engineers, I can tell you that having a degree at all tells me a lot about your work ethic. Sure, I'd prefer a comp sci background, but your degree is nearly as good. It's an indicator of how you think.

You know what other degree I see a LOT of in SWE? Music. I've hired countless music majors.


I have the opposite experience, almost. I've hired and trained lots of people with CS degrees who think they know everything and barely know the basics.

I massively prefer people who flunked university and just got a job writing code because they could. University no longer trains people to think, instead it's about jumping through hoops and dealing with pointless administrative bullshit [0]. source: I have a Master's degree.

And yes, even better are the people who wrote code as a hobby, and then decided to switch career to become professional developers. Some of the best coders I know are in that category (though the best coder I ever hired taught herself to code while getting off heroin in a Glasgow slum).

[0] Ok, so yes if you're hiring for a large corporate I can see how this would appeal.


Sure universities train people how to think. But they're in the liberal arts, which is why OP finds some many SWEs with music majors. STEM is very transactional. Liberal Arts is more about teaching you how to think and communicate.

The problem is too many tech bros have been pissing on liberal arts for 30 years. And now people are looking around and saying 'we have too many tech bros'.

My college years were spent reading various viewpoints, bringing them together, and synthesizing them into a coherent narrative. This turns out to be very helpful when it comes to solving problems and analyzing security incidents. I've found it more useful than that semester of C+ the new hires took for their CompSci degree.


> STEM is very transactional. Liberal Arts is more about teaching you how to think and communicate.

Are you able to elaborate on what you mean by these statements? What does being able to think mean and how would one be able to demonstrate that?

Do you think the only way to learn this is in the liberal arts?

> too many tech bros have been pissing on liberal arts for 30 years.

Your comment seems to be pissing on STEM. Am I completely misreading what you're saying? STEM and the vocational or mechanical arts have been pissed on by the liberal arts for a lot longer than the last 30 years.


> the best coder I ever hired taught herself to code while getting off heroin in a Glasgow slum

Those words bust the biggest bias I realized I had/have - against addicts. Thank you very much!


I said she was a great coder. I didn't say she was trustworthy. She eventually left the industry to go be pretty at gamblers in a casino where she could earn a lot more money for a lot less effort. My co-manager's blatant sexism also contributed to this. I often wonder whether she got back into coding, but lost touch years ago (this was pre-LinkedIn obviously).

"Never trust a junkie" is still very good advice.

Talent at coding doesn't automatically come with the personality or the temperament to be a good career software dev.


To provide a third vote: My midsized company barely considers people without degrees, even if they have extensive technical work experience. Example: I had to battle hard to get somebody considered for an entry-level non-technical role, and they ended up being rapidly promoted within engineering once they got past the recruiting screens.


This is my current difficulty - I work as a neteng for a large MSP in my area.

I quit university after my 2nd semester co-op during undergrad (to work at my current firm), I have since been promoted four times and now work as a senior engineer (though I cannot technically use this title). Trying to move firms now after working for 5 years, It is incredibly difficult for other firms to accept that I've been working in the field successfully given that I do not have a completed degree. On one hand, I have skill now that I could have never earned in school - on another hand I may have gimped my ability to move deep into the upper half of the first six figures salary.


Hmmm, have you had a lot of coworkers move through over the last five years? Following one of them to a new place is probably the easiest way to change jobs and build your resume.


I feel your pain. I've fought against this before.

I think it's because of the salary level - like HR/management cannot get their heads around paying someone who doesn't have a degree the kind of salary that developers get these days.


Wow. Pretty strong opinions here.

Completing a degree means you can commit and deliver, IMO.

Instead, leaving for writing code just because you can tells me that you took the short path, and that your missing basics (the real ones, which teaches you University) will knock at your door some day.

My 2 cents.


> Completing a degree means you can commit and deliver, IMO.

Not completing a degree doesn't mean you can't so this statement doesn't tell us all that much.


Not sure. As I said in the other reply, if you don't finish it, provided that you don't face major practical or financial issues, to me it is a red flag on being able to commit and bring something to conclusion.


As it stands it's a theory of yours. Now you need some actual data to back it up. It's a bit dangerous to reach conclusions based on a hunch, you might be biased after all.


I am definitely biased by my values, and I value finishing something once you started. Always ;)

Then yes, I might be of course proven wrong, I just gave my 2 cents on what not finishing a degree tells me, including my bias.

Then you could be a false negative, in the sense that you might have not finished your degree but be able to commit 100% on other things. However, as we all know, spotting false negatives is very hard and who hires don't like these bets if not in very particular circumstances, as it is going to be their fault if the person is then not a false negative but a true one. With or without backup data.

I think is no coincidence that as far as I can see the OP basically got the "finish your degree" as first and foremost comment.

Don't take me wrong: I have been a false negative and an outlier my entire life, now I love it, but in the early days I really wished someone told me what I am saying now.


> Then you could be a false negative, in the sense that you might have not finished your degree but be able to commit 100% on other things.

I'm not projecting my own experiences on others, I just take issue with your claim. Studying and working are very different beasts, I think it's very much possible for people to not finish degrees yet be really good employees that finish their tasks as agreed upon. The incentive structure is so different that the two can hardly be compared. Not finishing your degree, ignoring personal/financial issues, tells us nothing about their work performance.

> However, as we all know, spotting false negatives is very hard and who hires don't like these bets if not in very particular circumstances, as it is going to be their fault if the person is then not a false negative but a true one.

Yes that's hard but that's a very different issue from your original claim. It's a good reason for a recruiter to go for the person with the degree instead of the person without the degree, but that still doesn't mean that the person without the degree can't commit and finish their work.

> I think is no coincidence that as far as I can see the OP basically got the "finish your degree" as first and foremost comment.

He has 3-4 months left of a 5 year education, of course people will recommend him to finish his degree. There is very little opportunity cost downside.


Sorry, the "you" was not referred to yourself by any means, it was a generic "you".

My original claim was not an actual claim, it was just what not finishing something one starts tells me. A sensation. And by "not finishing" I do not mean trying for a bit and then quitting, that's of course OK.

What I meant is not finishing, after investing vigorous effort, because one gets "enchanted" with something else (e.g. "oh look I can code in javascript and build a website, who cares about finishing studying the basics, I don't need them anymore!").

By the term "finishing" I implicitly assumed to be near the finish line. If then this is not a symptom of poor commitment capability, I don't know what else it could be.

On another angle, the comment to which I responded originally basically said "University does not teach you anything valuable at all, just quit and go writing code" and here I strongly disagree and will always do.


>> I am definitely biased by my values, and I value finishing something once you started. Always ;)

What do you do when it becomes obvious that the thing you started is now irrelevant, or was poorly-conceived, even mistaken, when you started?

Genuinely curious. I've walked away from a lot of projects because I learned while doing them.


I don't want developers who continue doing something even when it's blatantly the wrong thing to be doing.

Flunking out of university is not the "short path". It's the hard path. Getting a degree is not difficult, or even hard work. It's the easy choice - the thing everyone expects you to do.

I don't want people who follow orders and do what they're told. I want people who are prepared to make hard decisions, take the less-travelled path, do what they feel is right and not just what everyone else tells them is right.

I want someone who can actually code, and not someone who has a certificate that says they can code.

My 2 cents.


I think we are just talking about two different things, and that you have in mind "coders" and "developers", not software engineers or data scientists. But the OP was talking about the latter, not the first, where I can to some extent agree with you.

I saw it many times: javascript kids or self-taught backend Python "engineers" falling extremely short when it came to scalability, algorithmic complexity, or just abstracting concepts.

Similarly, I saw several self-claimed "data scientists" not even knowing what a non gaussian error distribution means.

Not knowing this stuff jeopardise your work and the projects you are working in.

Then, if you are telling me that your interview process should spot these shortcomings at the same level a university degree can, then to me this sounds a bit unrealistic.

However, if you need someone that can write code to pass the unit-tests that some one else wrote without taking any architectural decision, than OK I can agree with you, but it does not sound much of an appealing career path IMO.


Completing a degree means you can commit and deliver, IMO.

So does a lot of other valuable and still relevant lived experiences, and they come without the price tag.

But we all already know that.


Sure, if you include the price in the equation then this makes things different, you are right. I got biased by the nearly free University we get in Europe.

However, if you start something, I think that it is a good attitude to finish it, provided that you don't face major practical/financial issues along the way.


However, if you start something, I think that it is a good attitude to finish it

I 100% agree with this. I've just got a bit (maybe a lot) of chagrin towards the sometimes strident mentality that college is the only meaningful way an individual can prove they possess such a capable characteristic, or that completing college is an indicator that such a person will retain such a characteristic throughout their careers/lives.

It's useful as a snapshot of an individual's educational accomplishments for sure, and more power to them for that accomplishment, but I will always have a bit of reticence about the application of "has degree" past that.


You think degree is important? I am trying to finish my PhD. But I don't want to stay in academia after I finish. Would my degree be helpful in getting any SWE jobs?


I have a Ph.D. and am not in academia. The higher degree opens up opportunities for challenging positions, but you will probably need to show basic SWE capabilities also


It depends on how far out you are. Finishing what you start is always a "good" sign. That's what a lot of people look for.

With the OP, he's 4 months away from finishing his degree. In the grand scheme of life, that's a "blink of an eye". There is no point not to, and (I don't agree with this at all) people judge you differently if you have a degree vs. not.


In most goal-setting advice, Steve Jobs comes to mind, having a reputation for being a finisher is the most valuable attribute.

Employers basically hire staff to get stuff done. The rest is details about specialization, experience, skill-set, etc. All of which is rendered irrelevant if you don't get the jobs you are assigned done.

Re: a PhD -- ideally you should ask the question why you want one is before you start. Cursory research quickly reveals that academia as a career track is very challenging. You don't need a PhD to be a great SWE. A PhD is training to be a researcher and an expert in a specific field.


it's an interesting talking point but that's about it in most cases. If you can find a role where some domain knowledge is related to your PhD subject, or they need the skills a PhD requires (i.e: academic writing) then it'll be very valuable, but a PhD in most places wouldn't actually add much value in the day to day: most SWE work is nonacademic.

Thinking to my own experience, PhDs are pretty uncommon but of those I've worked with, some are brilliant, and some are terrible -- just like non-PhDs. I wouldn't consider a candidate with a PhD better than a non-PhD candidate, but then some people would love to hire someone with a PhD. I'd say on balance, it's a positive to have, but I would never recommend someone pursue a PhD as a route into a SWE role. A year of hobbyist programming experience is enough to get a SWE job.


Depends on where you are. I think in Europe it is more important than in the US.

But I see anything above Bachelors as a personal preference (with a few exceptions). If you want to finish PhD, then go for it.


If you're trying to finish a PhD program, I'd say it depends how much you want to finish. "I did a year or two and academia sucks" is a perfectly normal place to tap out, but full STEM PhD -> SWE is also pretty common. If you just spent three or four years writing specialized code to simulate or analyze your PhD topic it's quite possible to parlay that into an entry level SWE job.


I think it will help you get roles, I don't think it actually helps in doing the job, and in my personal experience has a negative correlation with being a good software engineer (not necessarily on skill, more on delivering what's actually needed).


The negative correlation is because how most PhDs do not focus on SWE skills isn't it? But that group are probably not interested in coming to SWE either.


In my experience its because they are more interested in researching interesting things, rather than delivering the project/task they are assigned to. Basically jump down every rabbit hole they can find!


Yes.


A lot of startups are starving for people who have experience even if they don’t have a degree. I’ve worked with compsci PhDs that spent hours/days doing something that 3 years of experience in a heavy industry will teach you to do in a few minutes using a different method or more tools. Sure advanced degrees are needed for some frontier type things but in practicality they have very little up on someone who is passionate with coding and has worked with veterans in several companies.


It's more that if the only thing stopping you is that you've realized you want to work in a different field[0] then while getting that degree may not be necessary or even useful for itself, it does just make a lot of things easier and more straight forward further down the line.

Any time you have a situation where people are filtering large number of candidates impersonally, from hiring to immigration to dating apps, some of the time you'll be blocked for not having a college degree.

Sure, you can find plenty of start-ups or other smaller shops to apply to; maybe you'd even prefer to work for people who can see past a degree or lack thereof. If your life falls out that you can't get a degree or just have better options on the table than starting or finishing a degree-granting program, it's not the end of the world, you have plenty of options and opportunity. But it's still probably worthwhile to keep all the options you can if it's relatively little extra cost.

[0] If you're epsilon away from completion, if you've already paid for your final semester, if you're not in actual danger from staying in the program, if you don't need to get a job yesterday because you've run out of runway for living expenses, etc etc.


How do you get a software engineering job as a physicist? I'm one and I tried applying for a few (mostly with titles like "machine learning engineer", etc.) and mostly received no responses. For comparison, when applying for "data scienist" or "quantitative analyst" (in finance) jobs, I got many offers. Around here, the SWE people seem to assume that physicist can't write good code.


What country are you in? When I graduated in Elec Eng in the UK there were plenty of big companies like banks, government, utilities taking graduates of all kinds to train them into software engineering. I've met plenty of SWE with degrees in history, music, or people with no degree who've started doing manual testing or admin and got into automation and then software. Equally, if you already have the skills and can pass their test I'm sure they won't care what degree you have, physics shows a high level of technical comprehension and analysis as well as hard work.


The CTO of my last company has a degree in anthropology, so this tracks.


Agreed.

And honestly, finding an entry-level SWE job with a degree in Mathematics + a background in data science is probably easier than finding an actual data science position.


This is very true, software engineering with a Mechanical Engineering degree here...


You have just started your career. I have plenty of experience in software dev, having hired, managed, coded etc, your future isn't anywhere written in stone as you'd think. You seem very worried about the situation and it's definitely clouding your mind. Drink some tea and breath, all is good(as it can...)

It doesn't matter if you degree is in math if you want to work anywhere in computing: software engineer, data science, AI, IT support or anything. If you dislike working with Data Science feel free to try different jobs.

I'm a foreigner living in Germany and to net a job here you likely need some sort of seniority(read: 4 years working in X Programming language or something from DS) before people start considering you, but given how I know how living in a third world country feel like, and how ambitious people usually are when they live in such conditions, I believe you'll do just fine.

Try different things in IT. If you think SWE is a path, try it! Don't feel too attached to present outcomes, let's say you end up needing 1 year to find an internship in SWE, just accept and go with the flow. Of course, that is considering you are eating properly and surviving.

I know we can't choose like rich american kids, but you definitely have a great future ahead of you and many options

If you want we can have a call(email on bio) and you can ask any questions, I relate a lot to having the same kind of questions when I was at university and I wasn't even dedicated or successful as your beginning. I just stuck at it for a while and did what had to be done and I'm here Today, I work for a company, get paid well, live in a first world country and I believe all of this is in your reach, just enjoy the current moment as well, don't live in the future. Enjoy the adventure.


Your degree does not define you. People change careers regularly, and by the time they’re 40 they might be so removed from their degree that it becomes nothing more than an interesting topic for a party conversation. “Oh, I majored in so-and-so, can you believe it?”

The only way you can screw up is by staying in a field long after you’ve realized it’s not for you. It’s crazy to keep doing something you don’t want to do, for your entire working career. Whether it’s from the sunk-cost fallacy or feelings of shame or just complacency, it’s a sad thing.

It takes courage to be honest with yourself and make a change.

(I’m in marketing now but got a brutally difficult degree in naval architecture. Can you believe it?)


I can't speak about the technical side of the equation, but I'm someone who also worked very hard in a field before switching career and I get feeling like your previous efforts were for naught, so I wanted to weigh in. I can only tell you that the work you put in wasn't for nothing, even if it feels like it for now.

You're learned things about yourself (what works for you, what doesn't, and why). You've learned how to apply to job posting and the best ways to do so. You've acquired work experience and human experience which will serve you. Your university and faculty allowed you to learn how to handle high levels of work. You acquired a work ethics and a discipline which will be precious to you. You didn't put all that effort in for nothing: you grew, and you have a life experience which will be precious in your future job interviews (and in your future work!)

My previous experiences couldn't be more different from what I do now, but I still feel how important they've been to me: they shaped my mind, my way of thinking/analysing problems, and my ability to learn. I wish you the best of luck!


I understand that the "the work you did was not for nothing" angle of reading is comforting, but I have to disagree. Sometimes, and this may or may not be the case with the OP, but we are missing the details, we work for nothing or very little. Yes, we get something done because every minute of life is not a minute we are dead, but not being honest with ourselves often leads to more disappointments down the road.

It took me too long to change careers (from academia to technology), and I regret not making the change a few years earlier. I'm still alive, I have a very well-paying job, the past is in the past, and I could say that "I did the best I could with the information I had available to me at the time."

But being honest about my bad choices allows me to not be careless when I'm at the next turn in the road: telling myself that, whatever, even though I made a mistake, I learned something, is a good way to accept a mediocre life.


> I understand that the "the work you did was not for nothing" angle of reading is comforting, but I have to disagree.

I have to disagree. If you read carefully, they said,

> You're learned things about yourself...

This point alone means "the work you did was not for nothing".

Your entire past determines who you are right now, what you can change is the future. The meaning of a past event is determined by how it has taught your future self to make better decision. So if it takes them to have a job experience to know they don't like Data Science, then that's what is needed to happen to them for them to make a different choice.

I think you're projecting yourself to OP frankly because you said

> I regret not making the change a few years earlier

OP is switching right now just after a few months.

And your talk about honesty have nothing to do here (nothing wrote above is suggesting that.) May be it has something to do with your past but that's not the context here.

Lastly, just to point out another fundamental difference between you and OP: they are not even graduating yet. So we are talking about time spent learning A vs. B. So your "honest truth" is that learning A is "for nothing" is obviously wrong (I hope we need not arguing why, especially in this age where things are getting more and more interdisciplinary.)

This reminds me something a prof. told me when I was undergrad. and asking him advice on optimizing what I chose to learn. He answered me by saying nothing you learnt in undergrad. is going to be useful in real world, so feel free to learn anything you are interested in!


"So if it takes them to have a job experience to know they don't like Data Science, then that's what is needed to happen to them for them to make a different choice."

Or maybe, if they had people taking them seriously instead of providing this kind of "everything happens for a reason" paternalistic comments, they would have known it before spending time walking down a path that was not the wrong one.


> It is not about projecting my experience (I was not answering to OP, but to a comment) or "about the meaning of past event". I believe paternalistic attitudes sound good because words are comforting, but they are not helpful, they lead nowhere. And I provided a personal example.

My reply is to your comment of '"the work you did was not for nothing" angle of reading is comforting'. So that's why I mention "about the meaning of past event" because that exactly proves that the statement "the work you did was not for nothing" is truth, which is one of the reasoning whom you reply you used.

I'm not exactly sure the definition of "paternalistic attitudes" (not English native), but if just looking at what the word means, I would think something like "it's going to be fine"/"it will be ok" would fit more, but again not the comment from whom you're reply to.

> When I was having doubts about my academic career, what I was hearing from my advisors was "don't worry, I am sure with your CV you will find a job", "the important thing is doing a good job, then they will call you". And it made me very uncomfortable, I wanted to say to my advisors, will you please skip the comforting fluff, won't you? This is serious.

> OP wrote: "I'm quite depressed now because I've put enormous effort into switching to DS: I applied to 80 job postings before I got my first internship, and I feel this is for nothing now."

> And the comment I was responding to read:

> "You've learned how to apply to job posting and the best ways to do so. You've acquired work experience and human experience which will serve you. Your university and faculty allowed you to learn how to handle high levels of work. You acquired a work ethics and a discipline which will be precious to you."

> Someone is applying to 80 jobs before getting an internship and the comment is: "You've learned how to apply to job posting and the best ways to do so". To me, this attitude is very off-putting, it is very HR-like, it infantilizes the adult in trouble. Can you imagine losing whatever game 20-1, and when asking for help, the answer is: "you did a good job, you learned how to score, I am sure it will get better".

I really don't know why you view it this way... because I think the above statement is true. Just to also pull in some personal "failure", I once worked a summer job as a kid that's purely commission based, and guess what—I earned nothing from the entire Summer. But that experience is "money can't buy" and indeed I learnt something from the job itself too (like those coaching thing, and about the industry), not just merely an experience.

> "You didn't put all that effort in for nothing: you grew...".

> Again, is this not talking like you would to a kid?

Well, then I hope everyone's heart states like a kid and continue to grow... come on, OP doesn't even graduated. What's wrong to be reminded we grow? Why wouldn't we remind ourselves we are still growing. Stop thinking like someone "graduated" and never need to grow anymore. I mean this probably is about different world view on things, so can't argue with that...

> It is not a critique of a person who commented and I have no doubt they are very well intentioned. It is just that I see this infantilizing attitude creeping in in multiple places, from the corporate world to private life, everything needs to be reassuring, comforting, "now close your eyes and go to sleep". Typically ending with a "good luck".

I think the way you paraphrased is very different from which you're replying...

> "Your entire past determines who you are right now, what you can change is the future. The meaning of a past event is determined by how it has taught your future self to make better decision."

> This is both a tautology and non-actionable psycho-babble that helped exactly zero people in the history of humanity, but feels quite good when delivered.

This probably is related to world view. But first of all, just to state that this is Physical truth (assuming we understand casualty correctly) and whatever social science or other domain you're in, you cannot escape this physical truth (that your entire past determines who you are right now.)

Now what should you do with that truth? You can dwell on the past and think how things would have been different had I did XYZ. But you can't go back in time to change it. So this is meaningless.

Does that mean you should never regret on anything? Depending on what "regret" means. If "regret" does not mean you wanted something in the past change, but something you'd change to do differently in the future, then I think this is good "regret".

So I don't understand where you're coming from, because this entirely is not about feeling. It is about realizing objective truth and reflecting on how you can deal with it.

> "So if it takes them to have a job experience to know they don't like Data Science, then that's what is needed to happen to them for them to make a different choice."

> Or maybe, if they had people taking them seriously instead of providing this kind of "everything happens for a reason" comments, they would have known it before spending time walking down a path that was not the wrong one.

I disagree. This is 馬後炮 (\~hindsight in English.) The case of OP is quite typical. A lot of people have different fantasies about their dreams until they entered the field and realize it is not what they thought. Could OP, given their past, be able to know about it before taking that path? For a different person, they may not. But given the same person with the same mindset, same world view, same believe or whatever, how would they knew before taking that path?

That's why the one your replying to and me think that "You're learned things about yourself" is important here. For some people, and per person given some other things, they need to experience it in order to gain that insight.

In short I think this summarize well: you're against "paternalistic attitudes" but we (whom you reply to and me) are against hindsight. The feeling that one could have done better can in many cases be hindsight and we need to be careful about that. That's also why I mentioned about projecting, because in some sense projecting is "hindsight to a different person."

Edit: this HN line break is killing me!


A bit late -- terribly sorry -- but yes, KolenCh, you've expressed my intent pretty well, and often far better than I would have. I know I'm shaped by my regrets or failure, and I've grown a lot from them. Does that mean I celebrate them as happy? Of course not. I don't think they happened for a reason, either. But I do think that I've learned and grown from them. They've made me a vastly different person, better and stronger. Hindsight is always 20/20. Either you beat yourself up about not being a clairvoyant, or you trek on just a bit wiser.

Nobody is telling OP to continue on a path they hate. They're young; they have a lot of options. Given their achievement, they seem bright, hard working, and they have gained a lot of experience in many fields. When I was in college, I thought every choice I made back then would have life-lasting consequences in every other field of my life; it was liberating to find out I was very wrong.


There's many Data Science role which are actually poorly understood Data Engineering roles which it sounds like you "might" like more - dealing with pipelines, writing a lot of sql, wrangling bad data, making it go fast and scale for some platform engineering team.


I think you put a lot of effort in, and as a result you learned where your real passion lies. Good!

Many people I know, including smart ones, took a lot longer than you to find out what they would like to do than you. You may found further areas (other than SWE, or other sub-parts of computer science) that you may like even better, and life is long enough to try 2-3 things.

Finish your degree, because it's always good to finish what you start: people who do not know you will have to judge you by your paperwork, and if they can see "whatever he started, he finished, and he did so well" that is going to help you later.

I read your post carefully and you wrote that you like making things. Have you considered doing software development for embedded systems? In that space, you can interact a lot with physical systems, which you might like - whereas in other parts of SWE you often work on cloud machines that you will never see or touch.


I would consider it one of your specialties as a SWE. There are plenty of startups that would love an engineer who understands data, considering how devastating a bad SQL query can become over time, and how difficult it is to verify data.

For your next job just find a developer position.


This comment is dead on. I’m SWE who builds data/optimization systems and someone with this skill set would be a great hire.

Even if you wanted to get totally away from data most any modern system is going to need to interface with data systems at some point. Your skills would be super valuable.


I agree completely with this SWEs who understand data are extremely valuable. It sounds like you have enough hobby experience combined with your current work to get a SWE position. But, like other commenters have mentioned finish your degree first! Having a degree, any degree will open more doors for you.


Maybe you can transition to ML-Ops : it's building stuff around Data Science pipeline, and it's better to understand why it needs to be built.


Finish your degree and don't sweat about your current job (not making little of the dire situation in your part of the world ofc). 90% of the Data Scientist work is Data Engineering so you are doing the right thing. Kaggle and others are like conferences - there are specific trainings if you wanna do good in a conference that won't get you far ahead on the job life. You can do both. Don't tell people that you are not fit for DS before they telling you what they are looking for tho. As to switch to SWE after your degree, keep doing what you do - experiment and apply. Be safe.


As others have said, lots of really good SWE people started out with degrees in other things. I’d normally say finish your degree because in the short term it’ll be easier than having to explain things in every interview and open doors to larger places that don’t care about explanations. Longer term it can matter less by making sure to build up a portfolio of successful projects and keep learning.

On the other hand, the situation right now changes things and I can’t in good conscious recommend that to someone in your position. It’s a weighty decision and you have to make it based on what you think is right for you.

If you’re interested in working on Cloudflare on R2 (which is my team), Workers (my org) or anything else, shoot me an email at my HN username without 123 (vlovich) at cloudflare.com.

Edit: also feel free to reach out and I can share my personal email if you want to just chat more generally. My family escaped Russia in the 90s.


It sounds like you'd very much enjoy working as a data engineer. Data engineers are actually more in demand than data scientists in most place right now, so you're in a good position if you choose to go down that path.


Can you try to aim for something like an ML engineer to begin with? To avoid overloaded terms let me explain which kind of figure I think of. Specifically, I mean the kind of people that are in charge to take a proven ML architecture, try to apply it to the problem at hand, and potentially work on serving infrastructure to host that model (or plugging it into some Data pipeline for batch use cases).

There is a bunch of pure SWE work in the serving part and still requires some math background that, thanks for your education, you seem to have. This should allow you to get exposure to a lot of pure SWE-backend tasks which could allow for a full transfer into SWEland later on.

However, I am not sure how common these figures are in the industry. I work for a FAANG company as an ML Eng like I described, but I aware that not all companies have such people.

Finally, I wish you the best of luck in getting an EU passport!


1) as others have said, get your degree.

2) look at data engineering

Either on specific jobs or systems (map/reduce, streaming, databases etc).

Three, you have been given a gift. You know what you don't want and some things about what you do. Nothing you did was a waste. Focus less on the specific goals and be in the moment. It is great that you have industry experience, even before graduation. That is where you will do/did a whole bunch of learning. Also, don't let this specific job color your whole view of DS.

Peace


Agree with other posters : finish your studies. Get the badge for your CV.

Have you considered ML Engineering? This involves integrating models into applications so that might satisfy your urge to create rather than analyze & model?


First bit of advice, you're so close to graduation make sure you stick with it and graduate - finishing your course shows that you can learn and that you see things through.

Once you've graduated don't let the fact that your work experience is Data Science based put you off for applying for SWE positions. I've worked with a lot of software engineers whose education is in a different field, so switching over is certainly possible.


Congrats, you're better than most university students I know!

Being so much close to getting your degree, get it! You are almost there!

Besides, when you have your degree you're going to be above your (average) peer because of your real-world experience in Data Science.

If you can continue working and get your degree that would be superb. Once you have 1 year of experience, I think you could search for much better jobs.

My advice here would be to try to move your career path to Machine Learning Engineering. It is a relatively-new mixed-discipline, mostly SWE with some DS and DevOps. There is a coursera course that treats these topics, take a look to it once you have your degree [1]. There is also need for backend engineers with some DS skills. Try to learn Django/Flask/NodeJS/Go and with your DS experience, you're good to go.

Also, get out of Russia as soon as you get the degree and also, get the EU passport as fast as you can. The political situation is going to deteriorate in the following months. In fact, I would try to immigrate to the EU once you have your degree.

Advice for your future job searchs: Do not get un-motivated or depressed because of not passing the interviews (not I don't use the term "fail"). Most positions are already assigned and the rest of the interviews are a way to avoid nepotism claims or other criticism (or even legal repercussions). You won't pass 90% of your interviews, not because of your skill-set, but because there are a miriad of reasons for you to don't be chosen: another candidate is better/asks for less money, position is canceled, HR don't click with you, etc. Don't get discouraged and assume you're going to have to make many interviews to get a position, that's the game (unless you have FAANG experience), I'm afraid.

Good luck and keep rocking!

[1] https://www.coursera.org/specializations/machine-learning-en...


Do not transition to SWE thinking it will be more "interesting" or "fun". Although it appears to the outside that SWE is more interesting/fun, that's only true at junior levels, when no one expects anything out of you. If you want to progress in your career, you will have to transition to a senior engineer (needs to get things done with the least creativity possible) or management (spends all day in meetings). Every career path leads to this, even data science.


I agree with you. The feeling that grass is greener might play a role here, as I've already seen the 'ugly' side of DS, but not of SWE

But I thought I could easily come back to ML if I want to after SWE jobs given my prev experience. From inside the industry, I see that companies really want Data Scientists who know how to code properly


Agreed with the current top-level comment: finish your degree. You'd be surprised at how easy it is to move around early in your career. I have a degree in supply chain management and started as a supply chain analyst, but now I am a data engineer and operations researcher.

I too have worked as a Data Scientist but grew bored of it. You can get 95% of the way there on most DS problems by throwing a linear algorithm (favorites being GLMs and GAMs) or Random Forest variant at the data you have, and maybe doing some hyperparameter optimization with k-folds or similar. I've found the data engineering aspect of data science to be far more beneficial...you'll get far more out of thoughtful feature engineering than you will out of algorithm or hyperparameter tweaks. Leave those to the PhDs.

The second thing I would point out is that if you really do love Math and solving hard problems, you may want to start looking into Operations Research (aka Mathematical Optimization). There are tons of really cool problems to work on that will actually stretch your imagination. And unlike Data Science, where a quality resume reads like "I increased accuracy by 23%", a good Operations Research resume reads like "I saved my employer $300M dollars a year". Those are real numbers from a previous job, BTW...even incredibly efficient companies have lots of low hanging fruit where massively impactful decisions are still being made using human intuition or other suboptimal heuristics. Again, finish your degree, but if it is someone you'd like to look into, there are ways to find jobs that will get you adjacent to and perhaps directly working on Operations Research problems.


Data science is an oversold profession. When studying it, you learn really cool things; Bayesian models, reinforcement learning, AI, all the trendy stuff. In reality, most of the data scientists end up spending almost all of their time interacting with horribly designed, decade(s) old databases and the analysis part of their job is mostly just plotting the mean as a function of time and doing logistic regression over and over again.


Btw this isn't a problem specific to data science, it's how education works a lot of the time. Getting a computer science degree, you'll learn a lot of cool things but then a lot of your day as a developer will be spend gluing framework APIs together. In a medical degree people learn tonnes of interesting and advanced stuff but lots of doctors spend all of their day entering data into a computer, writing the same prescription for antibiotics over and over again and telling people to rest.

I feel like data science gets called out disproportionately for something completely normal.


I can relate to this. The process of studying ML algorithms, how and why they work from the mathematical standpoint was really fun. But the process of building models themselves seems quite boring to me


Spot on. "Data science" and "Machine learning" are indeed hyped up terms.

Most of the work is basics statistics, some SQL and poking at a ML library until you get the output you wanted.

Unsurprisingly, the day to day work can be very underwhelming.


i spent some time in "data science", back when it was just called "research", in a corporate environment.

95% of your value as a "data scientist" is figuring out how to squeeze diamonds from tons and tons of steaming piles of sh*t, and that kind of work is basically just filtering, collating, collecting, organizing from disparate data sets with different fields, data types, formats, some of them with varying degrees of accuracy. it's not fun, but very few other people are doing it, and the result is valuable to a lot of people, so it pays well.


Hi there, as others have said, finish your degree!

Second: Nothing is for nothing! :)

You learned something, you learned you didn't like something after you thought you did. Welcome to the rest of us, this is completely normal. It happens to many, many people.

Now you are in an exceptionally great position to switch to something else with little to no effort.

Data engineers or even ML engineers, people who combine in depth knowledge of data, statistics and SWE are probably one of the hottest job candidates globally right now. There are absolutely not enough of them.

I am based in Berlin, where you will easily find an internship or entry level job in data engineering or backend engineering with your degree and a EU passport. Also, we have a sizeable amount of Russian expats in Software Engineering in the city, so after living here a bit and networking within the Russian community you should be able to quickly improve your choices of places to work at.

If you want, feel free to send an email to gbx the "at" sign mailbox dot org. Happy to answer any questions about Berlin you might have and put you in touch with a Russian ex-colleague who's in Backend.


A thought: what you have is a particular set of skills. What you do with those skills may bring you more fulfillment than the act of using them.

Maybe telecom isn't for you. Maybe you'd find happiness in doing data science for an NGO that is saving lives in Africa, or an early startup that needs their second "data and data infrastructure" person to get the company bootstrapped. Or maybe not- that's just one thing you think about.

At the same time, nothing is wasted. You've learned stuff. Hopefully, you will continue to learn stuff your whole career, your whole life. If it happens that the first major skill you learned wasn't the one most critical to your career, that's okay.

Graduate with your degree. It serves as proof that you can learn stuff and not have your life fall apart for a few years.


I feel similarly about data science and I'm already a few years into it. But I don't think that's too relevant. Also, I don't get how people can study at university and work full time but I've heard that a few times from Russians so I just assume that it's a thing.

Positives for you:

- you're still at university and you already have work experience

- you haven't sunk years into a career you don't like

- you're employed and earning some money

- you're figuring out what's for you and what isn't

- you have some coding experience

It really seems like you should look for a SWE job, I don't think there's much more to it. What makes it difficult is everything that's going on in Russia and the fact that you want to move to a different country. But on every other dimension it seems like you're in a great spot.


My background is actually in Physics where DS seems an obvious choice. Although I didn't like experimental Physics much where people do lots of statistics. So I tried to shift focus on DS but I never really got off the ground, usually when I had the chance to work on something DS related it wasn't fun at all. (Also as you mention, model building seems not to be too popular) So I worked for years as Full stack engineer but shifted towards Backend. That I find most rewarding, sounds like Backend is also interesting for you. So I recommend applying there, I think the hiring stage is still competitive for people starting but far less then DS


How did you go about doing this? I'm most the way through a masters in Theoretical Physics and Applied Mathematics, and am going to be looking for jobs here in Ireland soon. My courses this term are pretty much all mathematical modelling over data science because they seemed more interesting, though I've also taken a module specifically on data programming with Python and one with Machine Learning with Python. Currently taking Advanced Computational Science, which is basically solving PDEs and models, as well as Climate & Weather Numerical Modelling course. I dropped Statistical Modelling and Maths of Machine Learning. My masters thesis is kinda a mixture between the two, making a model of how we can use statistical physics to predict collective behaviour and then testing it and validating it, etc. (though that latter might change given that it was supposed to be focused on Ukraine, where my supervisor had done it before after the 2014 annexation of Crimea).

I'd much rather do modelling than DS, even though I feel it'd be much harder to get a job with that. Or if I wanted to move into engineering. Basically, just looking for any advice for how you went about it.

I can work in Python and know enough JS to be dangerous. Built some stuff in the past for Irish-language learning, but it's all old and poorly implemented. Would also be willing to do other stuff for portfolio, etc.

Sorry for hijacking your comment, it's just what I'm struggling with now.


No worries! I guess I stayed very much on the theoretical side of things with not that much applied stuff. So I started working on the side while studying (also realizing that it's quite rewarding) and also tried my luck with a Web App. But later I looked for a fulltime job, created profiles on Stepstone and Monster. So recruiters were calling in and I went from there. Probably nowadays it makes sense to create a LinkedIn profile and as well of course write companies directly. Indeed.com has a lot of job ads, btw it's normal if job applicants only match 70% of the required skills.

Portfolio is good to have, esp. smaller companies will be happy to take a look at it. Large company usually have very standardized processes, your degree is more important and then it depends how interview and challenges go.


A lot of people have given good specific advice, so, let me point out that you are young, and while you may not like your exact specialization right now, you've still got quite a base of skills that can be leveraged into numerous other positions. Try to not feel bad. Try to let the large number of options given in other posts here some time to sink in, and marinate your subconscious in the realization that you are not trapped, but in fact standing in front of a wealth of opportunities.

You have to soak your subconscious in that information because it is slow to realize things like this, and it needs to be reminded many times a day for a long time. This is the core of truth behind the "self-affirmation" self-help movement. As with many other self-help movements it oversells what it can do, but it can do this. You will need to repeat to yourself many times that you have many options. Your conscious mind may feel stupid, but your subconscious needs to hear this many times, so consider doing it.

The first opportunity didn't work out. That's fine. Frankly, it almost never does. Careers often need a few years to get going anyhow. Remember that coming out of school and getting the job you're going to have for the rest of your life is the exception. Even the people going to FAANGS or whatever the acronym is this week often burn out and leave and do other things, after all.


I think some of the other posts have covered advice regarding the transition to SWE very well.

You write you are: > in the process of receving EU passport

This threw me off somewhat. Does this mean you're an EU member state citizen currently living in Russia and applied for a passport in your home country? I'm not sure I understand what you mean otherwise. Aquiring citizenship (for a passport) is either very expensive or requires permanent residency for a number of years.

[edit] For clarification I changed EU citizen to EU member state citizen.


If you can prove that your grandparent was e.g. polish citizen it is relatively straightforward to get a polish passport. Plenty of people like that live in former USSR


From what I understand:

There are countries in Europe that are not a member of the European Union. Eg: UK, Switzerland, Norway.

From what the OP said, they are from Russia, and studying in another eastern European country. (Russians (as well as plenty of non-Russians) have a tendency to go to Europe/UK/USA/Canada etc for higher studies I think.)

Russia is not a member of EU.

The eastern-European country the OP is studying in is probably a member of EU, and from there the person is trying to acquire an EU passport.

I'm guessing OP wasn't studying in Ukraine (which AFAIK isn't in EU), because then they'd have bigger problems at the moment than data science seeming like a waste. (By the way, I see unconfirmed reports that Ukraine has just been made a EU member. Like, today).

tl;dr: non-EU citizen trying to acquire EU citizenship.


> By the way, I see unconfirmed reports that Ukraine has just been made a EU member. Like, today

This does not happen overnight. Also it would be all over official news outlets and the website of the european union.

[Edit] The absurdity of that statement has triggered me a bit to be honest. It seems so unrealistic for me as a German that the EU as an organization is capable of such a reaction due to to it's structuring and the process involved, that even suggesting it on something like hn without some sort of source with current event being what they are seems like either trolling or an attempt at propaganda. I do understand however if your comment was made out of lack of knowledge of what the EU is. The world is a complicated place and we all live in our bubbles.


> The absurdity of that statement has triggered me a bit to be honest.

Oops I'm so sorry I never meant any offence.

I did mention it was unconfirmed.

Anyway, for everybody who's reading: I was wrong. It looks like Ukraine's not a member of EU at the moment.

You're right I don't have a deep knowledge of EU or Europe; I shouldn't have said anything.

> either trolling or an attempt at propaganda Oh please no. I have nothing to do with propaganda. Nor was I trolling. (Which makes your statement a "false dichotomy fallacy").


All I saw was studying in eastern europe and "lives in Russia". Russia is in eastern Europe although usually not referred to as an eastern european nation.

I am aware of the EU and it's member states, I'm a little confused as to what might have implied I did not. I am from an EU member state.

I was just curious about if and how they planned to aquire citizenship because it's a lengthly process and they mentioned they were in the process while living in Russia. Usually residence permit is the way to go (and years later citizenship). It was rightly pointed out that if you can prove descent from a citizen it might be easier.


Well, if you're interested in a fullstack job, we're hiring at Gouach in Bordeaux (France) and are looking for people who like to build, and like to tackle climate change and sustainable mobility :)

https://gouach.com and https://www.welcometothejungle.com/en/companies/gouach/jobs


Lots of good advice given. I echo what many have said about Data Science..it's an overloaded phrase that means anything and everything to everyone. It's important to understand the context in which that the person is applying it.

I did a mid-career change from working decades applying advanced control theory to Data Science. The transition was very natural in that many of the curriculum and principles taught overlapped naturally with Data Science (what it was called at that time). To me, I stress the SCIENCE part of data science that involves designing experiments, developing theory, writing the code/drivers needed to drive the hardware, building the hardware, etc. Unfortunately, my definition has become the outlier. Side note...I have noticed that DS is becoming interchanged more and more as a very advanced BI/BA role, which further dilutes the conversations. Basically, what I'm getting at is that it's never too late to change...just gotta keep asking questions and failing (in a good way).

I'm glad you realized this earlier rather than later. Based on your ideal job description, I think you would make an ideal back-end developer...possibly full-stack?

Good luck!


I don't know about the job market in Russia, so my perspective may not dircetly apply to your situation.

In my experience, smaller companies might be more for you. The job positions are often more versatile and varied. I imagine you are more likely to find a job there where you can combine SWE with your DS knowledge and still like it. In such companys your tasks typically require you to solve real business problems all the way through, for example: "We have some sales data. Can you write us a tool that helps us decide where to focus our marketing efforts?"

But firstly, as others have pointed out, since you already invested a lot of time into DS, finish your degree as fast as possible, and then take the opportunity to build a portfolio (even if it is pure DS) and a professional network to help you find a better job. I do not think that it should be too difficult to transition into SWE with a DS degree; and after a few years of professional activity, no one is interested in what you have originally studied anyway.


> How would you recommend me to switch to SWE the fastest way possible?

First thing you should do is see if you can pick up an SWE job with your current skills. When I got my first software job (in 1996, writing test scripts in the aerospace industry) all I knew was a little bit of matlab, basic and pascal. See what's out there! There's more to software than FAANG


There is so much more to software development than just data science. I think you haven't been introduced to any interesting systems projects.

Maybe try to work on a database or a compiler for a few months if you can manage the time? OS projects work too, but it's more difficult to readily find interesting OS projects nowadays.


Congrats on the progress you have made, and also for realising what your preferences are.

First: Finish your degree - a valuable and important signal to employers is that you finish things, not start and stop whenever you have a change in emotion. It's ok to feel discouraged sometimes, but it's never ok to quit what you're supposed to finish.

Second: Your data science experience is very valuable already, and so once you start learning SWE, you have a good mix of skills that many of your peers with only data science or SWE won't have.

Third: I still like Ruby on Rails for web app development, and there is still a ton of opportunities out there for employment on it. So think about learning that. To incorporate data science into web apps for production, there are a lot of options, and Rails will keep you productive with moving forward and learning more in that field.

Good luck, and congrats on your upcoming graduation!


1) Finish your degree 2) Get a entry level role in SWE or internship (your degree is very compatible with that) 3) Program something you can demonstrate in the mean time (will help get you in the door and build skills) 4) keep building and applying 5) realize you might not like SWE either, that’s okay you can switch again.


I don't think anyone doing full-time data analysis at a telecom will think "this is what I want to do in life."

It looks like you've done almost all the hard work on something valuable. One boring job shouldn't discourage you from an entire career path. Similar data analysis techniques can give you very interesting results.

It's easy to extrapolate your first job into your career, but that's almost never, ever the case.

Now, to answer your question: how to switch to SWE the fastest way possible: In your current job, and in the time you have left at school, optimize for the next job you want. Do you have any projects in either that could be done with more or less software development? I suggest you try as much software development as you can. Keep doing this at work after you finish school, too. That'll start steering the boat in the direction you want. It won't take much, there's plenty of demand for SWEs, so the more you can show you can do, the more you'll find demand for it.

Your biggest asset for switching to SWE is what you're about to complete, and the work you're already doing. You just have to finish filling in your resume with more SWE work.

Also, keep doing side projects, and if possible, open source them on github and they start becoming a portfolio to show alongside your resume.

Also, data science uses a lot of software. You can start adding to, or writing your own tools to help your day job. Even if it just makes the SQL better. You can generate SQL, or depending on your DBMS, add new functions to the SQL system that you can then use. Again, the reason for that isn't just to do your job better, but to make a better demonstrable SWE skillset. After you get your data back from SQL, can you do some post-query analysis in another environment, like python+pandas or apache spark? That's all software development, and frankly can be easier to do than trying to do some analysis in SQL alone.


>How would you recommend me to switch to SWE the fastest way possible?

It's very simple - finish your degree then apply for intro SWE positions. You'll have no problems with your background and skillset. You'll find other people with math degrees working as SWEs in industry.

Just make sure to finish your degree.


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Finish your degree, doesn't matter if it's Math and Econ, lots of these majors get into software as a profession.

If you have experience with SQL and are good at it you can find work everywhere with that alone.

If you want to become more full stack learn one of the more popular web app front ends, however I will note that I've used SQL for nearly three decades, the only other tech that I can think of that existed in 1992 and is still fairly mainstream today would be shell scripting and PHP. All the modern web tech, javascript-y stuff is shifting sand and it will change or be replaced as fast as you can become competent at it. It's exciting at first, then frustrating, then demotivating. Or at least that's how it seems to me.


I work with data scientists, SWEs and various flavours of engineers.

My advice would be to finish your degree. You're close and it's worth it.

After that, branch out into some specific domain that interests you. It will give you an incredible edge over all vanilla DS / SWE people. Plus, it'll make work interesting.

Pure SWE after a while will give you the same feeling as you're experiencing now. You're just building web apps for some startup dweebs, or shuffling endless Java classes in some grey corp.

So yeah. DS skills will come in handy, so will SWE skills. Great to get that base in your education. But long-term, find an interesting niche and get good at it. Just not anything super-obscure as not to limit your options too much.

Good luck!


My heart says ML/DS, but when I start learning my brain says stop it :) If you do not enjoy it, give a pause and relax. ICT is huge and spans across different industries/domains, with many different roles and responsibilities. Start as a SWE of anything you are familiar/comfortable with, after gaining noticeably experience, change to the role/domain/technology of your choice. Always remember today’s greatest technology might turn to a legacy/irrelevant after 5 years. Your foremost goal is to finish your degree, unless you have a quest to start your own business. Then get a decent SWE job to gain industry experience.


Take up a specialty that sits somewhere between SW and Data Science? I'm a freelancer specializing in knowledge graphs and see a world of promise in this area. It's still a very young area but promising. Get deep on some graph databases, learn the ropes with W3C semantic web, and start looking for companies that have ongoing graph/semantics projects. All the big tech companies have significant investments in this area, Pharma and science are not far behind, enterprise will bring be joining in soon as they realize their data landscapes are hopeless. And of course, finish your degree.


European companies are desperately looking for IT people. Try smaller companies, not just the well-known ones to get started. Some even take on people before/without a graduation if the coding is good. All the best!


The work may sometimes involves SQL, and that's very good knowledge. You can get lost in optimizing the queries, and it can even become it's own line of work. We used to call them DataBase Administrators, and I guess the job may still exist somewhere. However, you should be careful a lot of places in the industry are actually hiring for a position called Data Analyst which is sometimes confused for Data Scientist, or the reverse where an analyst is hired for DS role...

Finish your degree, obviously... you can pivot to other jobs if you like, but once you find a real DS role it may improve.


Few things you learn are ever truly wasted. Especially DS knowledge when you are switching to software engineering. I know data science and machine learning are all the rage right now, I work in a data science unit and assist the really smart phds around me and build the platforms they are working on. Be happy that you found out know and not later. Software engineering is amazing. You can do infinite things and your actually building stuff. Sorry that you don't feel good about it right now but building things is so much fun and so rewarding, you are going to be okay!


First, as everyone here said: finish your degree, it will surely help with relocation and job search.

I have a very similar experience to yours (didn't like the analytics side of Data Science) and my advice would be to look into ML engineering roles. ML engineering is heavily SWE-oriented, sort of an intersection between Data Science and Software Engineering. I switched to ML engineer and I totally love it, you get to learn tons of cool SWE stuff (Docker, kubernetes, linux, cloud, ci/cd) and you're still close to newest ML research, which I love :)


I was a CS major and during my first "real" internship, I was feeling the same way. I dreaded coming to work. It was a long day. I was working in a windowless office, writing PL/SQL to generate reports and trying to learn COBOL for some legacy billing system. I was not offered full time work, fortunately. Everything worked out when I got a job doing Web Development with .NET and JavaScript. For me, just the change in technology was enough. And I needed to grow up a little more. I still work as a developer and my days fly by.


I studied maths too, then spent 2 years in a data science role and in the last few months moved to data engineering which has aspects of both DS and SE and turned out to be what I wanted to do all along.


hello!

finish your degree as other people said!

most of my friends pivoted HARD after graduating to something completely different: think geology--> marketing, neuroscience--> UX, etc.

find the components of the job you like, and try to dig into those. You now have a really lovely skillset that will be useful in all areas.

you can also always go back to school for a masters, phd, etc.

Good luck! I pivoted last year from medicine to neuroscience through going to a phd program, and it was a very tough transition, but I am so so much happier now. You are still young, you've got this.


I've worked as software engineer for the past 16 years. My degree was completely orthogonal - physics - although I took some software courses on the side. Never stopped my progress.

Finish your studies, and then find an employer. Do a few online courses if you feel you need to brush up on your skills.

Your degree is most valuable by existing, not being in any specific field.

There are of course position that can be quite strict from qualifications point of view, but don't let that stop you. There are many, many others.


Switching from DS to SWE will not be very hard for you I dont think. Additionally having the DS background can make you extra marketable, especially for smaller companies where a broader skillset is more valuable. If you wanna get some skills with SWE, I would build & deploy some project. Dont worry about the business side but building a rails or nodejs project from scratch and figuring out deployments etc will give you a lot of answers to interview questions.


You might want to gravitate more in the machine learning engineer direction. So much of ML is building the data, training pipelines, the serving environment, model tracking, evaluation, promotion, and other general infra around modeling. Many data scientists are more analyst-plus, and don’t have strong engineering skills. But large scale ML needs more of the latter. As long as you can AB test, you don’t need strong statistical skills to tease apart effects.


Of course, one should consider, there is for sure a bright future for an analyst with math and economics background from Russia in the west.

For the Company or another..


Pursue what you love. If DS isn't your thing , quit it. At least you've given a shot. If you love SWE just seek for SWE!

And I know this is opposite of what most say here but I haven't seen any benefit of my CS degree, and no job ever asked for my university, so I'd say focus on real world not the university, but again this contradicts with many of the opinions. Probably a cultural thing.


Here’s my advice. If you still like working with data then you should look into consulting where you get to work on different projects across different domains. You have to build up your toolkits even within data science. Mastering something like GIS takes awhile and same goes for time-series/finance. And only way to do this is through consulting gigs.


The grass is always greener...

But no reason to be depressed. You should be proud about the effort you put into getting this position. It's never lost. I can't speak about your particular situation in Russia, but as far as switching to SWE, it should be easy. Some people switch careers in their 40s. As a young graduate, it's very easy to change path.


Finish your degree, then pursue computer science. Understanding statistics and data is a super power for a software engineer. There are a lot of data-adjacent software engineering jobs. Telemetry, data pipelines, data visualization applications, maps, apply your cs and ds skills together for an awesome combination.


It's no bigee, don't take it too serious, your still figuring out what you want to do, that's normal. Be pleased you have learnt something, better now than in 10 years! And what you have learnt isn't going to be completely wasted, I'm sure it will help you as a SWE.


Migrate to bigquery, twitter runs on it. No storage cost and you can plugin google datastudio, bigqueryml and automate a lot with cloud-functions. Show them how to do better and graduate on that. They will thank you for it because of the complexity you have removed for all your colleagues.


I feel ya, I was a data engineer at my previous job, and I hated it. In the end, it boils down to the fact that data scientists simply use the tools, while the SWEs build them. Trust your instincts, and follow what you are passionate about, instead of chasing hype/hotness in tech.


With Data Science experience interested in SWE, my first thought is that you could focus on a related specialty area, for example Data Visualisation. Your data science background will mean you have strong foundations to build upon. Datavis expertise in increasingly sought after.


Start leeting and learning algo/DS. Should be no problem to get an entry level job in 3-6 months. In 1-2 years switch jobs and you’ll be doing well. Btw I should add that you’re making the right decision DS is a bad career for reasons I won’t get into here.


> Btw I should add that you’re making the right decision DS is a bad career for reasons I won’t get into here.

Can you tell us more?


There are plenty of SWE jobs adjacent to ML that you'll probably fit right into. I specialized in networking in grad school and was always building web management tools for project. Turned out liking the app development tasks better and went that route.


There are lots of places where a SWE with a solid DS background will be very welcome, even if you've no formal education, if you can show some github repos or other projects you've made, getting a nice enough position is possible.


You discovered you had poor match quality. And the ds experience will help you anyway.

Read the book “range why generalists triumph in a specialized world” if you want to feel good about switching careers once or even multiple times.


See if you can transfer to the data engineering team. They do a lot of coding and you DS background is a big bonus as DS is a client of DE.

I recently completed the transfer from BA to BI and then to a BI that does DE job.


Nothing is written in stone, it's never too late.

In IT knowledge is important, but the ability to gain knowledge is even more important. Just finish your degree. This way you can prove, you can gain knowledge.


Don't drop from your path just yet. Try working for another company in a data scientist role, in a different industry. Something is missing but may be found elsewhere.


> The thing I like the most is actually building stuff with my hands, and I think SWE is a better fit here.

Is this a metaphor? SWE is terrible for building things with your hands.


Just finish the degree and apply to swe jobs. Tailor your resume to mention previous swe experience and as long as you can pass the interviews you’ll be fine.


Finish that degree. With your math background, it won't be any problem to pick up the algorithm stuff you need to pass a whiteboard.


Become a machine learning swe. It's an amazing blend of stats / match and raw engineering. It's a ton of fun


You're already a SWE, just don't apply to data science jobs when you're looking for your next thing.


stay positive! all DS skills will be transferable to normal SWE, the best SWE are all multi-language and strong SQL never goes to waste, lastly - many of the best SWE would be even stronger with some DS competencies, so keep at it and I suspect you'll wind up in a pretty awesome place.


As someone who made a similar transition but in the opposite direction, (from iOS to web frontend to ML), it seems like the best thing is just to start doing more SWE work. It feels like there is neverending demand for entry level SWE in the US, and any background that can pass the interview is welcome. I don't know what the market is like in Europe, but I would not worry about being able to pivot.

The work you did was almost certainly not a waste. The SQL you learned is going to be incredibly valuable to small companies looking for "fullstack" or backend roles too. Definitely puts you above bootcamp grads that only know how to put together a UI. And understanding statistics let's you run proper A/B experiments at large companies, or apply to "data engineer" roles building critical data infrastructure.

All these things are also just valuable even if all they taught you early in your career is that you liked doing something else. Some people get PhD's before realizing they hate the field and then the sunk-cost-fallacy (or student loans) force them to pursue a career in it anyways, it's wonderful to have clarity on what you like so young.

I would probably just finish your degree if you are close, because I think it could make getting visa sponsorship in some countries easier, but I would just read some tutorials for the kind of SWE engineering you want to try on the side, and build a small portfolio project with the tech. It doesn't have to be anything fancy, just a to-do app even if you want to do web frontend in a popular framework like React, for example. I think there are probably MOOCs to look into that pick a project and walk you through it even, but I don't think you have to go that route. Just a little effort to demonstrate to employees you understand the tech you chose, and for you, to make sure you actually enjoyed worked with the tech. I am thinking on the order of 1 weeks work. Throw that on your resume and just apply to the kinds of jobs you want. You are almost certainly over-qualified for many.

The good news is that the worst is probably behind you. In my experience (in the US), SWE is way way easier to break into than data science, you just need to finish a small minor project. This wasn't wasted effort, it's a small part of your overall career and it taught you valuable study skills and how to do hard work!

I will also close by saying, I imagine things can be rough in Russia right now. It is possible the depression you are feeling has multiple contributions and will pass when you change your environment, or your environment evolves, and is not all from the work you are doing. These last few years have been rough for a lot of people around the world. I would say you have built up valuable skills that you will almost certainly use again in your career, and not attribute all of the reasons to feel bad to your early career just yet. You have some excellent experience going for you.

Good luck! Let me know if you choose web development and want any advice on that career in particular. I would look into fullstack or data engineer roles personally. My email is my username at hey if you want to chat more.




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