I have recently been accepted to a top five math PhD program. The department seems to have a good mix of pure and applied math, and there are plenty of opportunities for collaboration with other departments (Stats, CS, Econ, etc.)

I am most interested in pursuing math more on the applied side of things. Moreover, I would like options outside of academia once I graduate. Looking at the previous PhD alumni, this does not seem to be a problem - anyone not in academics is doing pretty interesting stuff in finance, data science, consulting, machine learning. However, I want to make sure I am not missing something along the way that these students did which enabled them to have broad and attractive job prospects.

I am especially interested in Analysis, Probability, Stats, Machine Learning, Econ, Mathematical Biology, Cryptography, and Applied topology. I would be happy to do work involving any one of these.

My questions are these:

  1. What should I do during my PhD to be able to have good non-academic job prospects after graduating? (Would something like a PhD minor be helpful?)

  2. How does it differ by field? If I want to do something like quantitative finance, what do I need to do versus if I want to do something like data science?

  3. How can I find out more information about question two. As things change and evolve, how can I find out what it is I need in order to be accepted for positions and jobs involving areas that interest me?

I am not sure if I am exactly asking the right question, so if someone else has suggestions of what I should be asking, please suggest.

Note: There are a number of questions on this site that ask similar questions, ("I'm doing math but I want to go into industry") However I think my question is rather different. Firstly, I am hoping to pursue research with applications during my PhD, rather than focusing on super pure math. Secondly, I am asking this question before I have even started my PhD, hoping to know what I should do before, during, and after my program. Most of the other questions basically have the theme "I did a PhD in pure math, now what?"

  • Your question seems pretty broad, especially since you haven't even narrowed down a field. It's also a bit borderline for being on-topic to me, because it's not really about academia but about job prospects outside academia. In general though, if you do a PhD in an applied math area where applied means applied to something done in industry, you are unlikely to have any issues with job prospects based on what you've done or haven't done during your PhD.
    – Bryan Krause
    Apr 17 '19 at 22:21
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    I think this is a very relevant, and legitimately scientific question, even if not so good for this site. The fact that the majority of math PhD's currently seem to be getting jobs outside of academia has only recently been widely acknowledged, and there seems to be very little public discussion about what this might mean for graduate programs' content, etc. Maybe this question is too math-specific, but I don't think it is "too broad". Difficult, yes. Apr 17 '19 at 22:26
  • Not a real answer, but a place-holder: until some years ago (I do not have precise details), perhaps a majority of math people did go into academe, at least initially. As quite a few of my own students from years ago found, in those days a PhD in math from a good school was a ticket, in itself, regardless of specific PhD topic. The point was that it was pretty difficult to do, and required being able to do basic math reeeeeally well. Truly great general analytical qualifications for any sort of job. But... nowadays, yes, you are competing with lots of other people with... [cont'd] Apr 17 '19 at 22:32
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    The problem is the objective itself is extremely broad. How will any one person here know whether it is better to supplement your phd by learning to program versus learning to predict sticks versus learning french? People can only suggest directions that are practically orthogonal. Apr 17 '19 at 22:33
  • [cont'd] ... comparable qualifications. Having a PhD in math from a good school is not longer a golden ticket out in the real world, though it's still (as far as I can tell) better than lots of other pedigrees. So, yes, plausibly, targeted study could be good. However, established curriculum is inertia-laden, in violent contrast to of-the-moment practices in banking, etc. The curriculum will surely not really keep up... Obsolete viewpoints are almost worse than ignorance... ?!?! I don't know. Apr 17 '19 at 22:35

Based on my own interactions with graduate students and post-docs, I would suggest:

  1. Develop skills that are useful to potential employers. This includes basic communication skills and a broad background in data analysis and modeling as well as buzz-word computer skills (R, Python, Deep Learning, etc.)

  2. Develop cultural-competence for the corporate world. Learn how to dress and act the part, preferably by immersing yourself in the corporate world through an internship.

  3. Have some examples of your work (besides your papers and dissertation) to show to potential employers.


Another important factor here is choice of advisor. Look through the faculty profiles and see if you can find a good fit. This would be someone with industry experience, or that has managed to assign their students to industry jobs past graduation. It would be good to be advised by someone who'll be able to help you get internships at relevant companies and direct your research in the direction you want.

In my experience, math PhDs (with a smattering of CS/Econ/Stats) are highly employable in industry, even if they err on the purer side of research. I know several people who studied pure math and applied their problem solving skills in internships with very good outcomes, let alone if you are learning applied skills on the way. Other soft skills that you acquire will be extremely useful in industry - writing papers, speaking skills, problem solving and so on.

PhD studies are also an excellent time to try out transitioning your ideas into startups. Most good universities have tech connections to help you do that, try to look into that.

Good luck!


Instead of thinking in vague terms about how your mathematical training can be applied in industry, I think it is much more fruitful to focus on problems in the real world that excite you. Most math PhDs pursue research problems by letting curiosity guide them. Things don't suddenly change just because you're going into industry. Particularly in the current era because of the tech boom, there are tremendous opportunities for bright, mathematically minded people in industry.

It isn't just power point presentations and talking to clients. Of course there's nothing wrong with that if that's the kind of thing you like. My point is just that mathematicians have a rare ability to think deeply and get to the core of a technical problem and many corporations are realizing the value they can bring.

If you haven't heard of them, two people to read about are Eric Lander and Jim Simons. Both started out as mathematicians and went on to become great figures in the fields of biology and finance respectively. It is notable that Jim started out trading in a discretionary manner and only later incorporated quantitative techniques. So rather than viewing "industry" as some monolith, think about what problems you want to solve and be confident that your mathematical training will give you a leg up.


I added a PhD minor in computer science to my mathematics PhD. It's helped market me for industry jobs. Every recruiter has mentioned it. One still needs to have the skills (and be able to demonstrate them in the interview) but the minor does seem to get you phone calls.

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