I’m a full stack software developer with about 10 years of experience building things like APIs, mobile apps, various backend services, SDKs, etc.<p>I’ve long been interested in finance and am always mistaken for working in finance (guess I just look the part).<p>I’m wondering if anyone here has gone from the world of software for the stereotypical Bay Area startup or large tech company to world of NYC quants and hedge funds. I don’t have a PhD in mathematics or some other extreme traditional qualification, but I do have lots experience building stuff.<p>I recently moved to NYC and would love to join one of these companies, especially considering the earning potential versus other companies.<p>Has anyone here made that move?
I worked for a few years in fintech (NYC) after I left SF (more than a decade working at FAANGs).<p>I'd say your experience as a full stack software developer is basically irrelevant. At the end of the day, for a typical non-leadership engineering role, the hiring decision is not going to be based on your previous work experience. They are looking for strong algorithmic fundamentals and the ability to think outside the box (I've interviewed for both in the past).
I have. The hedge fund world isn't really as enigmatic as they would have you think. It's the same as anywhere else: work at a reputable company, get an interview, do well. I don't think it's much different than working at a FAANG. Lots of ex-Google employees at Two Sigma, for example.<p>Things are a little different if you want a job as a quant than a software developer, though.
Just random thoughts:<p>Be pretty good at what you are doing (absolutely no need to be a genius though, at least for SWE). Classic Google interview stuff, although they do put emphasis on slightly different things.<p>Knowing maths helps, knowing low latency helps, but its not required - any quant shop needs a ton of normal software.<p>If you don't have friends in the industry, etc. going through a good recruiter might actually help.
<i>> How to get a job at Jane St., Two Sigma, etc.?</i><p>Which "job"?<p>If you are going for a role as a quantitative trader, then your job will involve building mathematical models for predicting the price of assets. You would need to study up on probability theory, statistics, and risk management.<p>If you are going for a role as a software engineer, then your job will involve building internal tools and infrastructure for productionizing the models that quant traders build. You would need to study up on data structures, algorithms, and systems design.
Info might be a bit dated, but, when it was a possible path for me, Jane Street was an OCaml house and did a fair bit of picking from Columbia grads who took the OCaml version of Programming Languages & Translators. Legend also says they would ask candidates to do math problems in their head while the interviewers crinkled newspaper and talked loudly. Fair to say they are looking for <i>exceptionally</i> skilled and sharp candidates.
The math PhDs are for quants, sounds like you want to work as a dev. I think they still have very high standards for those, but it's probably quite similar overall to getting a FAANG job.<p>Depending on their strategy and stack they may have specific backgrounds that they look for for some roles, eg telecoms signal engineering, networking, maybe compilers or UNIX internals, but it's probably worth just giving it a shot with whatever your experience is. A finance background isn't required, they probably also won't care if you trade on your own. So I guess the advice is just practice some LeetCode.<p>Since you asked about Jane Street, they're famous for using OCAML, so that'd be a good thing to look into if you want to demonstrate a desire to work for them specifically.
I ran a data science group at a major discretionary NYC based hedge fund. We were not a traditional quant fund, but hired many software engineers.<p>Here is my take on what it takes: <a href="https://magis.substack.com/p/what-makes-alternative-data-scientists" rel="nofollow">https://magis.substack.com/p/what-makes-alternative-data-sci...</a>
Leetcode and possibly these problems: <a href="https://www.amazon.com/Heard-Street-Quantitative-Questions-Interviews/dp/0994103867" rel="nofollow">https://www.amazon.com/Heard-Street-Quantitative-Questions-I...</a>