Math Math PhD prospects in industry

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A math PhD focusing on applied areas like PDEs, kinetic theory, and statistical mechanics can have strong prospects in industry, especially with programming skills in C++, MATLAB, or R. Understanding how to communicate complex mathematical concepts to non-technical audiences is crucial, as techniques like Monte Carlo simulations are favored in finance due to their explainability. While some believe the math-finance sector is declining, a PhD from a reputable program combined with practical programming experience can enhance employability in quantitative analysis roles. Self-taught programming skills applied in research may be more impressive to employers than formal coursework. Overall, practical experience and communication abilities are key factors in securing industry positions.
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I have some questions about what direction to take in grad school. First of all, I don't really think I'm going to pursue the academia route. With this being the case, I'm wondering what a math PhD's prospects in industry are.

I plan on pursuing PDEs and mathematical physics. Some of the professors at my school are very applied, I would definitely consider doing something in kinetic theory or statistical mechanics, but I would love to do something in QFT and PDEs. How will this affect my employability? I actually wanted to also take some Probability and maybe even work in Statistical Mechanics.

Any advice or input is greatly appreciated.
 
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It helps a lot to get a job in industry if you have some C++ programming skills. Failing that, being good with computer packages like MATLAB or R will greatly increase your employability.

One other thing that will help is undergraduate teaching. Something that influences what mathematical techniques do get used in industry is how well you can explain them to non-technical people. For example, mathematical techniques that involve monte-carlo simulations or Markov chains tend to be used a lot in finance, because you can easily explain what's going on to someone who doesn't have a lot of technical background. Things that involve QFT tend to be less used because it's harder for non-technical people to understand.
 
twofish-quant said:
It helps a lot to get a job in industry if you have some C++ programming skills. Failing that, being good with computer packages like MATLAB or R will greatly increase your employability.

One other thing that will help is undergraduate teaching. Something that influences what mathematical techniques do get used in industry is how well you can explain them to non-technical people. For example, mathematical techniques that involve monte-carlo simulations or Markov chains tend to be used a lot in finance, because you can easily explain what's going on to someone who doesn't have a lot of technical background. Things that involve QFT tend to be less used because it's harder for non-technical people to understand.

Hmm I see. I think once I pass my prelims I will take some programming courses, who cares if they are undergrad courses, I need to start somewhere.

I thought the math-finance world was really on the decline? How easy would it be for a math PhD from a top 15 program with good programming skills to get a job in math-finance or quant analysis?
 
It's my opinion that programming classes may not be the way to go. You can learn everything they teach in a fourth the time on your own and employers will want to know whether you can actually apply whatever you've learned anyways.

What would really get you traction is to be able to show some programming applied in your graduate studies. Saying you taught yourself the language and used it will be far more impressive than saying you took some undergrad class.
 

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