another phd student looking at the fork in the road

  • Thread starter Thread starter OxBlue
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Quantnet hello, I'm happy I've found you.

I am a 2nd year DPhil student with a recent growing interest in the quant space. My background is in Physics. I've decided that academia is not for me and am now looking elsewhere. Quant seems very interesting because I can make use of what I have learned over the past 6 years and make money :)

What is a likely career progression for someone with my background in quant finance? My concern, at least from my research, is that data science roles in quant has a relatively low ceiling given the specific nature of its job, and that it is hard to progress after a while. For example, it would be difficult for someone in data science to become a fund manager. Is this view valid, if at all? Though I enjoy working on the technical side of things, I hope to eventually move away and into more managerial positions. I don't want to be a 50 year old still writing and debugging code. I'm wondering how possible this is in the quant space?

Otherwise, thinking about getting an MBA and getting into private equity.

I should admit I don't have a strong background in programming (no C/C++). However I do know Python and Matlab well, or at least I use them everyday for analysis. My DPhil in on MRI Physics. My maths these days is also a bit slow as I haven't needed PDE, ODE in a while, but I'm confident that I can pick things up quickly and learn new items should I need to. I graduated from a top school in the US (in Physics) with a full scholarship and now at Oxbridge in the UK also with a full merit based scholarship.
 
I don't want to be a 50 year old still writing and debugging code.
LOL

Just you wait :)

My maths these days is also a bit slow as I haven't needed PDE, ODE in a while, but I'm confident that I can pick things up quickly and learn new items should I need to.

I don't get it; you are a DPhil in Physics and your maths is rusty??
 
I don't want to be a 50 year old still writing and debugging code.
LOL

Just you wait :)

My maths these days is also a bit slow as I haven't needed PDE, ODE in a while, but I'm confident that I can pick things up quickly and learn new items should I need to.

I don't get it; you are a DPhil in Physics and your maths is rusty??

Some maths I haven't used in a while is what I'm trying to say. For example, Greens functions, stochastic calculus. Mostly my work these days relies on Linear algebra, Fourier transforms, and Bayesian statistics.
 
Some maths I haven't used in a while is what I'm trying to say. For example, Greens functions, stochastic calculus. Mostly my work these days relies on Linear algebra, Fourier transforms, and Bayesian statistics.
What you need from Stochastic calculus, PDEs and ODEs is not that much unless you go to derivative pricing et al. What you know is exactly what people are looking for now.

P vs Q. P won. Read Meucci's article:

'P' Versus 'Q': Differences and Commonalities between the Two Areas of Quantitative Finance | www.symmys.com
 
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