this post was submitted on 12 Nov 2023
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tl;dr is it worth to obtain PhD title in order to get better DS career perspectives, even if it would require a lot of commitment and dedication?

I'm 25 yo, working full-time as Backend Engineer and also studying CS (specialization in DS) full-time. It's my final year and I'm already working on my master's thesis.

So here's the thing. After solid 5 years spend in IT industry as backend developer I come to conclusion that's not really what I want to do for the rest of my life. I worked at couple different companies (both startups and Big4), and I don't see any development prospects for myself in this branch of the industry. It no longer gives me that "sparkle" and feel of fulfillment as it used to. At the same time, during my CS studies at Uni I started working on some basic DS stuff, I wrote a bachelor's thesis about multiclass classification and now continue my work on that topic writing my master's thesis. Working on anything related to DS makes me feel like a 5 yo with a dinosaur atlas, I can spend hours reading research papers, searching for datasets and programming. I'd love to get a job in DS soon, but at the same time I'm still insecure about my DS skills. I also can't afford to get a "junior level" job in DS, as I already have financial obligations that must be met.

Here's what I came up with: first I'll sign up for PhD studies, during which I'll have a lot of time to learn, experiment, and I'll be supported during the process by my supervisor. During these studies I'd still have to work full-time BE or DS job (if I would find a DS job that pays enough to cover my obligations), which would be quite exhausting, but I'm used to working and studying 12 hrs a day to pay the bills and pass the exams. After I eventually obtain my PhD title, my perspectives for getting a highly paid job in the future should be much better, and I'd probably already have enough experience to get a regular DS job at any company related to the field of my studies. The only thing that makes me anxious about signing up for PhD is a fact that I have no academic achievements yet, I haven't published a single research paper yet.

What's your opinion on this? Does my reasoning make any sense to you?

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[–] bill_klondike@alien.top 1 points 10 months ago

Do it if you enjoy research. If you don’t, it’s not worth it (and you’d probably wash out).

[–] SirBlobfish@alien.top 1 points 10 months ago

I'd suggest looking into Master's programs (especially if a job can fund one for you)

[–] Longjumping_Tale_111@alien.top 1 points 10 months ago
[–] jedi-son@alien.top 1 points 10 months ago

It really depends on what you want and what value you place on doing a PhD purely for the joy of it. For me personally, I was able to get into the research scientist ladder with a masters from a top uni. Because of that I was able to enter the workforce sooner and compete for the same jobs I would've if I had done PhD. If your goal is purely to progress your career and make money ASAP then that's probably more efficient than getting a PhD.

[–] Important-Respond595@alien.top 1 points 10 months ago

I did my bachelor paper using machine learning algorithms, and if anything, I found out, that datascience overall requires educated people with phd or master degree at least, since the nature of DS is such that you really need to understand theory, because small change can really impact a final model...

[–] maskedpaki@alien.top 1 points 10 months ago

Not worth it imo. I was originally planning it after masters but now I don't feel like a huge timesink will be worth it.

Just keep working

[–] crouching_dragon_420@alien.top 1 points 10 months ago

I was told for research positions in most big tech, a PhD is required unless you are a superstar.

[–] AltruisticCoder@alien.top 1 points 10 months ago

My father worked all through his PhD, and by the time he finished in his early 30s, he was at the director-level in the company. However, that seems to be increasingly a rare occurrence as when I tried to do it during my master's, my supervisor nearly dropped me and forced me into basically just working at his lab. So keep this in mind if you wanna work during your graduate degree (and find the right advisor/group in that regard).

I also think a large point of value in doing a PhD is publishing a lot of cutting-edge research. To me, a master's with many papers probably positions you better for the jobs you noted than a PhD without any. Lastly, if you are talking about a PhD in ML, admission to top-tier program is ridiculously competitive; so you may wanna factor that in too.

[–] No-Introduction-777@alien.top 1 points 10 months ago

Working on anything related to DS makes me feel like a 5 yo with a dinosaur atlas, I can spend hours reading research papers

sounds like you should do a PhD. just don't expect a high paying job immediately afterwards

[–] sshh12@alien.top 1 points 10 months ago

Recently had to make a similar decision but as new grad whether to go directly into ML industry vs masters/PhD route. After speaking with a bunch of Machine Learning Engineers and Data Scientists in industry it my main conclusions were:

  1. Most people whether or not they went the PhD route were happy with what they did, where they ended up, and how much they are being paid (the exception being people who started PhD and didn't complete it -- that group regretted spending time on it)
  2. Most MLE/DS roles, especially now in the AI craze, are not researchy and are much more so applied in a way that a PhD isn't usually needed

Ended up going directly into an MLE/DS role and no regrets so far 1 year in and I honestly don't think I would've gotten a better/higher paid position having had a PhD.

[–] GenerativeAdversary@alien.top 1 points 10 months ago

PhD student here. I'm 100% in on it being worth it because of what I want to do in my career: research. Working at the cutting edge on mentally challenging problems is fun to me. I think this is more necessary for machine learning than data science, though I would suggest at least a master's for data science. It also really depends on the specifics of the positions you want to be in. The best thing to do is to start looking at jobs and thinking about career paths. Then, think about what you need to get there. Of course, things change quickly, so you might want to think about what jobs will be in demand in 5 years.

[–] BayesianOptimist@alien.top 1 points 10 months ago

Some phd programs give you a master’s enroute, and allow you to off-ramp from the PhD while still getting the master’s if you find out you don’t want to do research for the next 3-4 years.

[–] kbt@alien.top 1 points 10 months ago

It's not needed to work in the industry on machine learning projects. Maybe get a job doing hands on work in ML to get some experience.

[–] Lonestranger888@alien.top 1 points 10 months ago

Do what makes you happy. But try to find it in a corporate setting if possible. Find a startup at the leading edge that needs you, before they get bought by one of the giant companies. Perhaps they will support your phd. Academia is ahead in a lot of things, but high tech is moving faster now. In the AI race the big companies and larger startups are spending billions to keep ahead.
Find a niche doing what you love in that.

[–] P_Peterson75@alien.top 1 points 10 months ago

Thats really on you and what you want to use it for

[–] bob_shoeman@alien.top 1 points 10 months ago

tl;dr is it worth to obtain PhD title in order to get better DS career perspectives

No. A PhD involves 5-6 of training for academic research, which is mostly orthogonal to what is done in non academic industry positions.

During these studies I'd still have to work full-time BE or DS job (if I would find a DS job that pays enough to cover my obligations), which would be quite exhausting, but I'm used to working and studying 12 hrs a day to pay the bills and pass the exams.

This is the part where your expectations become wildly unrealistic and deluded. Not only is it unrealistic to balance two full-time jobs, it’s hard to imagine an advisor who’d want to advise a student who spends a significant portion of their time/efforts on things completely unrelated to their research.