How to become a quant for a PhD in Pure Maths student?


I am a PhD student in pure mathematics and have been drawn more and more to the investment industry. I have a solid understanding of the markets and finance, however, I don't really know any coding and definitely not the machine learning knowledge that is required from quants now. I was wondering if anyone has been in my shoes and what would you recommend me to do to bridge this gap before graduating from my PhD? I was thinking CQF or some other online courses whilst doing my PhD as I don't really want to do an MFE after PhD?

Quick intro/background, I did Part 3 of the mathematical tripos at Cambridge and now I am doing PhD in Pure Maths at St Andrews. I have had internships in finance/banking as well. I am mostly interested in quant trading and strategies.

Daniel Duffy

C++ author, trainer
Quantnet C++ course, for sure.
Depending on pure maths, it may or may not be useful initially.
ODE/PDE and numerical analysis.

And Python (QN has a course).

Lots of hands-on stuff.

I think CQF is more useful maybe when you already have a job?

edit what's the PhD topic called?
Last edited:
What year of your PhD are you in? In what area of maths are you doing research or planning to do research? If you’re doing or planning to do stochastic analysis/diff geo, harmonic analysis, pdes, etc I think if you spend some time learning C++/Python — as Dr. Duffy said above, the QN courses are good places to start — you would be in good shape to apply to summer internships in the summers before your 2nd to last and final years (there are some intended specifically for PhD students (at least across the pond in the states) - D. E. Shaw group).

As far as learning stats/ML goes, check out:

Last edited: