Tailoring Pure Math Ph.D experience for jobs outside of academia after

[l'Hôpital]

Hey guys!

Let me throw in who I am before I introduce my question. I finished my year of graduate school last May, figured out an advisor and a field (something related with Brownian motion on manifolds), and I'm overall happy with it all. No plans of dropping out, I enjoy the company of my peers, and excited to learn more!

Nevertheless, after much pondering, I think that I probably don't want to pursue work in academia, at least in the usual postdoc --> assistant professorship --> tenure. I'm totally okay with only minimally using (if at all) the pure math knowledge I obtained during my Ph.D . I see the Ph.D as my 'me time' and I'm ready to not use any of it if it comes to that point once I have a career
.
Given these facts, what should I do in grad school in order to not be unemployed once I graduate? From reading old threads, I understand learning programming is a good choice. How would I go about that, and most importantly, how do I go about proving that I have the knowledge, all while in grad school? What other things should I do? Where should I look for if I want to find internships? Most math jobs if I find seem to require the Ph.D and they are all academia. Not quite sure how to look for interships, haha. If it matters at all, I go Northwestern University. I'm open to any and all jobs. I just want to be ready so once my Ph.D is over, I have a nice job ready. I figure given that I have 4 more years, I should be able to succeed in this regard.

My hope is that if I ask early enough, the opportunities for the incoming year won't be missed!
Thanks for the help!

 

[StatGuy2000]

Hi there, and welcome to PF!

If you wish to pick up programming, my advice to be to either take courses offered at Northwestern, or study programming on your through online courses offered through EdX or Coursera. As for proving that knowledge, you could try working on existing open source software out there or by creating simple applications that you can save as part of your coding portfolio (in the same way that graphic designers keep a portfolio of their work).

BTW, your research field (Brownian motion on manifolds) sounds like it's a part of probability theory. Am I correct about this, and if so, how much of a background do you have in statistics? If you do, that may open up opportunities in areas like data science/data mining. Internships for financial companies may also be an option for you, if you are willing to work in New York or London. As for internships, have you tried applying to places like Bell labs or AT&T Labs Research? Or how about Microsoft Research or Google? I know of math PhD students obtaining internships there.

Hopefully I've been of some help to you. Best of luck on your studies and research!

 

[l'Hôpital]

Hey, I've actually been here for a while, I'm just...uh...I guess inactive lately haha. I've been here through all parts of my math career, even since I was a freshman in college!

I really like these ideas for programming. Currently, I plan on taking this intense course on Python in two weeks (it's some part of this 'Big Data' initiative. A week long course, 9 hours a day), but I do hope to be able to somehow keep applying it so I don't forget it!

My research field does indeed have to do with Probability theory. Unfortunately, I have 0 background in Statistics. I would love to do financial stuff, are there internships for that? How would I go about obtaining those interships/jobs? I will look at the places you have suggested. I didn't even know they had stuff for graduate students. Thanks for the names and information!

You've been a lot of help!

 

[homeomorphic]

Nevertheless, after much pondering, I think that I probably don't want to pursue work in academia, at least in the usual postdoc --> assistant professorship --> tenure.

Congratulations on steering clear of that.

You might want to supplement Python with C++ and/or Java, and R is good for data science stuff. You might just want to focus on fewer things and not try to do too much, since grad school is kind of intense. For a company like Google, they are going to want more computer science theory, particularly data structures and algorithms. Machine learning is another thing that's big in industry right now. There are courses for that on Coursera and MIT's opencourseware. Another interesting online resource that's really easy to learn from is Codecademy. I always felt like I should focus on learning math in grad school, but really, if you are learning stuff that is going to get you a job and gives you a safety net, it might not be such a bad thing if it slows you down, particularly if your goal isn't academia, anyway.

Some of the best mathematical jobs are the ones you get with advanced degrees in engineering or computer science, I think.

If NSA is your thing, they hire a lot of mathematicians.

 

[homeomorphic]

There are also tons of tutorials on youtube and text-based websites for learning the basics of Java or C++. As far as continuing to use it, you can always come up with fun things to experiment with in programming. If you are interested in game programming, it's hard to ever run out of ideas for that once you get going.

 

[homeomorphic]

Oh, and another thing. I'd recommend books like Effective C++, Effective Java, and Design Patterns: Elements of Re-usable Object-oriented Software, once you get the syntax down. That may help to avoid being seen as more of a hack who will write bad code, and interview questions having to do with that. There are also books and websites devoted to programming interview questions.