PhD Astrophysics to Finance

[Ari]

Hey guys,
So I'm just entering my 4th (of 5) year of my phd in astrophysics, and have been thinking pretty hard about going into finance, or another quantitative related field after graduating. A couple questions:

1) On the homepage is the thread "2015 quant job market: CDS is dead, booming data analytics". Maybe I should focus more on being a data scientist in (or out of finance), instead of trying to push into a dying/ultra competitive field? At my core I'm passionate about numbers and modelling (my day to day physics work), and so I don't need to specifically head into finance, but it seems like a good use of my skills. Plus I like people (which I don't see that often in physics other than a conference or something). Maybe push for data scientist instead? Although from a distance I see what the day-to-day is of a financier vs. data scientist, I'm sure it's not the same as actually trying it out. Any stark contrasts between the two that anyone (from their experiences) could point out to help me decide between the two?

2) For the last couple months I've been looking at job postings for banks, hedge funds, etc., and it looks like although I do learn a lot of the required skills from a PhD in Astrophysics (C/C++/Python, mathematical modelling, etc.), I don't think I could like, just drop into a finance/bank job right after graduation with my current resume. Starting this semester I'm going to start taking some quant finance/stats courses at my university, but still not sure if that would be enough. Taking a few courses (either for credit or auditing) is not the same as real experience. Maybe some kind of 1 year MFE program after my PhD would be really beneficial? Looks like that might be a useful transition mechanism (i.e. looks like you don't need that much finance background to get into an MFE program, but you are "certified" for the finance world coming out).

Thanks in advance,
Ari

 

[pingu]

call a head hunter and start looking for a job.

 

[C S]

Look at hedge funds and work on technical interview problems. There are a lot of small funds out there that aren't so concerned about work experience and have a good work environment for academics. It's not easy to find the good ones though since they are lower profile. That's one reason people often advocate headhunters, but unfortunately, nowadays most of the headhunters are just spam artists.

MFE is not worth it for anyone with a math-intensive PhD.

 

[Connor Whelan]

I'm currently interning at a large tech company as a Software Engineer, and I just recently had a long discussion with the Director of Analytics and Data Science because I also see Data Science/Quant Finance as two potential career paths (currently pursuing a BS in Applied Math and CS).

What I took away from our discussion is that Data Science, at least at this company (he seemed to have a lot of experience though), is not a profession an especially gifted physicist or mathematician can just waltz into and be a master at. It seems to be something that requires a very specific skill set, which includes machine learning, applied regression analysis, time series and functional analysis, probability and yeah pretty much all stats topics, plus programming skills (specifically python and R). Hiring managers usually have specific problems they are trying to solve and won't hire someone who doesn't have the necessary skills even if they have great experience in another field. I do understand there's a good chance that you, and other physicists, already have this skill set, I just felt it was decent advice and helped me get a better idea of what a data science job is like. You probably could get a job somewhere without those skills, but not necessarily a great company you'd enjoy working at, because you'd be smarter than everyone yet so frustrated that you have to take orders from them since they actually know more about data science.

On the other hand, people can correct me if I'm wrong, you have banks and large hedgefunds who actually like taking in some of the smartest people in the world (physicists) and coaching them up on how to use their talents to make them shit loads of money. So I think if you took a class or two on finance and stochastic calculus, and read some of the book on the quantnet reading list, you'd be in a good spot to land a quant job.

P.S.
It'd be nice to get an update in a few years when you've graduated and start working in whatever field you choose. I love physics and love the idea of doing an applied physics phd and research in plasma physics, and would probably go into quant finance if I can't find a job in controlled fusion research or something innovative like that.

 

[Ari]

Thanks for the responses guys, you answered the big questions on my mind. Especially to Connor Whalen for the inside insight into data science, really helpful. It struck me as well that you actually need quite a bit of background to break into (a good) data science (career), and probably nothing is going to be so smooth of a transition that I can just slap my resume on the desk and get a job.

I'll definitely be around here in a few years, and will provide an update whenever I feel like I've transitioned to that next thing.