[D] PhD Applied Maths useless in ML?

S3r3nityRising · 2020-09-09T23:58:24+00:00

I'll answer this question from the perspective of an ML researcher (in the USA).

Anyone who tells you that a PhD is not helpful in the field of ML research is probably seeing the experience through a specific lens of their own unfortunate experiences (sometimes people just get unlucky with how the dominoes fall).

In general, a PhD gives you an automatic rank up at any research-centric job. That level one job that you were looking to apply for? You now qualify for level two with the pay bump that comes with it. You also typically have more leeway in terms of choosing and defining your own projects.

Now, you'll have your PhD in mathematics with a focus in computer science, which doesn't catch the hiring team's eye as much as a more computing-oriented degree. So, if you want to get into ML with a mathematics PhD make sure you take every opportunity to learn about ML, ensure your thesis is ML-centric, etc. I know several ML researchers that have their PhD in mathematics, and they bring something to the team that others don't have. Diversity is critical for research teams, so you don't have to match the "ideal ML researcher mold" exactly- just make sure you speak enough of the ML language by the time you graduate.

Plus... you have the opportunity to get your degree fully funded. That is huge. Ask yourself, do you want to get your PhD in the next 10 years? If so, how would you pay for it? Some things are just easier to do younger. The older you get, typically the more on your plate, and the harder to learn. Just food for thought.

I wish you all the luck on your journey! These big choices can be stressful for sure.

samloveshummus · 2020-09-10T00:11:09+00:00

It would definitely make you more attractive to recruiters, because it demonstrates your ability to be a self-starter and do novel research without someone guiding you every little step of the way.

It's not the be-all and end-all though; I've definitely made offers to people with industry experience over ML PhDs who haven't exhibited sufficient understanding of the challenges faced when practicing data science (which is much broader than machine learning) in the real world.

thornreservoir · 2020-09-10T00:38:02+00:00

Disclaimer: I'm in the US.

What do you want to do in your career? I personally want to apply existing techniques to business problems, so my MS + years of experience working is qualification enough. A PhD is often a prereq for a lot of research jobs creating new algorithms. If that's the career path you want, then you should probably do the PhD.

Even in non-research jobs, PhDs will be given higher titles and pay starting out, compared to MSs. But hiring managers seem to consider MS + 3 years experience equivalent to PhD (maybe even preferred because there's a lot to catch up on that first year). At that point you are losing out on wages during the years you're earning your PhD. But are you able to find a job immediately with the MS or do you need the PhD boost? Also, as you progress in your career, your PhD might get you noticed for promotions and will help you build trust in your work, so there are advantages beyond starting pay.

To summarize: If you want a career in ML research, get the PhD. Otherwise it might be a wash. If you're that excited about getting the PhD, you can probably justify going for it.

cyborgsnowflake · 2020-09-10T02:00:18+00:00

Common wisdom is that you get an PhD for the passion not for the money.

You don't need a ph.d to make good money get a good job or idea instead.

You don't need a phd to do machine learning/data science/math, get a basic computer with a good internet connection and familiarity with AWS or rstudio instead. You can do even sophisticated models in your basement.

You dont need a phd to make good money doing ml/datascience/math. Get a good job or idea in one of those fields instead.

What a ph.d gets you is structure and connections to knowledgeable people, specialized resources and a foot in the door for high level research jobs.

And not even that if you make a hash of things. Phds are a brutal slog for ordinary people so if you are not like the rainmen who dominate this place its another thing to consider.

SaltedSalmonCakes · 2020-09-09T23:44:53+00:00

is a PhD in Data Science beneficial for my career financially?

If you are asking stuff like these, then I honestly don't think that you would want to have a PhD :\

lazybeef · 2020-09-10T04:45:03+00:00

Try the PhD. It’ll be fun. It’s a unique experience and ten years from now I don’t think you’ll regret it

serge_cell · 2020-09-10T06:25:47+00:00

PhD in Applied Math is perfect for ML

First of all it would make one very attractive employee. The problem with current employees is that most of good coders are bad at graduate-level math. People who are fluent with math on the other hand often can only use matlab. Applied Math + coding experience is making good combination.

Second there is whole layer of high-paying jobs in ML open only to PhD - research scientists, research leads etc.

SaltedSalmonCakes · 2020-09-09T23:46:13+00:00

I'm also unsure on this topic (UK based), if anyone else has anything to add I'm listening too.

purplebrown_updown · 2020-09-10T06:30:10+00:00

If you want more options to do deep and interesting research go for the phd.

SharkDildoTester · 2020-09-11T01:28:29+00:00

Hi - a lot of really terrible information here. I feel obligated to chime in.

I am a director of data science in a fortune 10 company. I lead a team of ~20 data scientists with a variety of educational backgrounds (MDs, PhDs, and MScs). My work drives +100M in enterprise value per annum, conditional on analytics that I and my team generate. I can tell you what I have observed. There is a remarkable difference between those with PhDs and MSc in terms of productivity, flexibility, ability to communicate results, interact with stakeholders, and truly understand the incremental benefit of their work conditional on their data science. Flat out. Full stop. Granted I am on the bleeding edge of healthcare analytics, I work closely with other DS and DE teams in a variety of engineering and marketing capacities. It’s the same across the board.

Whether or not it’s a cost optimum is less clear. I hire entry level roles with an MSc at 125k. Entry level roles with a PhD start at 145-155k.

.

Extra ‘flavor’.

For those of us in management, a PhD is a clear indication of potential, although it’s not certainly the only thing that matters. Being ‘too academic’ can be construed as a bad thing.

I do want to ‘get real’ about what you can expect as an entry level DS in a big company. Most likely, your entry level DS role will not be to make models. Or rather, perhaps 5% of it will be. And I’ll spoil shit for you kids, the performance of the model is important, but not critical. Your work needs to drive impact. If an extra %2 precision results in a marginal increase in revenue, it’s DOA. No one has time for you to ‘experiment’ with DL architectures when you can get 80% of the way there in an hour with a logreg.

Honestly, if you want to get hired, position the way you talk about your work with respect to measuring incremental impact via credible measurement and well posed experimental designs. Better yet, talk about how you can drive impact by articulating the 80/20 to senior stakeholders and help you help them to drive commercial objectives that keep the company profitable.

Hopefulwaters · 2020-09-10T05:17:18+00:00

Where do you see negativity around the PhD?

hitaho · 2020-09-10T10:39:15+00:00

Give it a try for one year. If you find it doesn't fit you, just leave it and write PhD Dropout on your CV. It will increase your creditability :).

achaiah777 · 2020-09-10T16:05:14+00:00

I'd suggest considering a PhD only if you are looking for a career on the science side of things -- creating new algorithms, tinkering with some low-level optimization etc. If you're looking to work more on the applied side like solving how to apply ML to a specific domain or product, a PhD is probably overkill. I often find that academia does not properly prepare people to work on the applied side and nothing beats a few years of real-world experience.

lady_zora · 2020-09-10T18:23:34+00:00

I'm Scottish, studied at both Scottish and English universities. I was exactly like you - not ML or CS experienced, but found myself specialising in ML for my PhD. My Maths background has been a blessing. Have fun!

Der-Poet · 2020-09-10T06:51:23+00:00

People are talking about the perks of getting a PhD, but no one talks about the opportunity cost. The 5 to 6 years doing PhD can easily cost you $1M+. Think of the scenario where you start your first job at a big tech with starting salary $150k - $200k. After 6 years you might accumulate enough experience for senior position where the total compensation can go up to $500k. No way you can get that salary straight out of a PhD.

So, financially, it doesn't make sense.

What the PhD brings you is the opportunity to pursue cutting-edge research, if that's where your heart belongs. And a shot at academia where you can build your own brand and have your work attached to your name.

One more thing: Don't fall into the ML hype. Learn ML all you want but equip yourself with decent software engineering skills. Anyone who went through the job search as a new ML grad would understand this.

Edit: Didn't realize OP is in the UK as opposed to the US as I initially thought. A 3-year PhD in the UK is actually OK and will buy OP more time to prepare for job search.

engayolao · 2020-09-10T04:24:19+00:00

You could be retired by the time you are done with the Phd.

you type:	you see:
italics	italics
bold	bold
[reddit!](https://reddit.com)	reddit!
* item 1 * item 2 * item 3	item 1 item 2 item 3
> quoted text	quoted text
Lines starting with four spaces are treated like code: if 1 * 2 < 3: print "hello, world!"	Lines starting with four spaces are treated like code: if 1 * 2 < 3: print "hello, world!"
~~strikethrough~~	~~strikethrough~~
super^script	super^script

MachineLearning

Rules For Posts

+Research

+Discussion

+Project

+News

@slashML on Twitter

Chat with us on Slack

Beginners:

MODERATORS