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This question will serve as the definitive community wiki of career anecdotes. Future career questions can be pointed here.

There are as many career paths as there are people. How did you get started in the industry?

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    $\begingroup$ Please see the linked question on Meta in the first sentence of this post. $\endgroup$
    – Bob Jansen ♦
    Jun 27 '20 at 5:25
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I first found-out about quantitative finance during my PhD program. Like most grad students, I was looking for an excuse to procrastinate from my dissertation. I began looking at the course catalog of different departments until I saw a course entitled "The Mathematics of Finance". The syllabus listed terminology I had never seen before, like Black Scholes. When I read-up on what options pricing was, I realized that this was an excellent application of my academic specialty: high-performance computing.

I applied to every job ad at an investment bank or hedge fund that listed a PhD in computer science. I eventually got a position doing statistical arbitrage on a proprietary trading desk at a bank. So began a ten-year journey of stat arb and HFT at various banks, hedge funds, and small prop shops.

Quantitative finance is a career of constant learning; I have had to continuously absorb new technical skills and domain knowledge. It's also a field with potentially unstable employers. The first three trading desks I worked at all shut down, which is why I have an enormous amount of skepticism for most firms in this industry.

Finance is ultimately a game of infrastructure, and most places (and people) are surprisingly bad at this. The only competitive advantage is time. As in, how much time did you spend practicing your craft? How much time did you spend building parameter optimizers, data pipelines, etc.? That's why I have no patience for people who claim they have to keep everything secret; almost no trading idea is transferable from one firm to the next without an enormous investment in infrastructure.

So for anybody who wants to enter the field, I would suggest that you learn as much background material as you can, including general finance, accounting, economics, etc. Also, get really good at programming. (The language doesn't matter; your boss will tell you what to use.) And while you will have to practice your math, don't get attached to any single technique or asset class. Ironically, despite learning of this industry because of Black Scholes, I have never traded options professionally.

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    $\begingroup$ I feel like there's a bit of a gap between seeing that a course in mathematical finance exists on your university page and applying for a job at a hedge fund? Or did you rely entirely on your background in computer science/Statistics? Can I also ask, do you think that your PHD has given you opportunities you wouldn't have gotten with just a master's degree in financial engineering or similar? $\endgroup$
    – Oscar
    Jun 26 '20 at 19:08
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    $\begingroup$ @Oscar Just apply for the job. No need to overcomplicate things. $\endgroup$
    – chrisaycock
    Jun 26 '20 at 19:23
  • $\begingroup$ What do you need to get a job today? I can't get one anywhere (I don't have a PhD - too late for me to get one) but can code in R and Python and implement statistical and ML models. I'm not necessarily looking to be a quant, but just be able to use stat/ML in finance somewhere. $\endgroup$
    – confused
    Jul 24 '20 at 4:15
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personally studied physics and ultimately converted to finance like many simply looking for a job.

just to be rigorous as this is what it's all about in this field, quant is not a job, it is more like a label.

it can mean pricing derivatives for the front desk of an investment bank, validating macroeconomic stress testing models in its risk division, doing bayesian inference for a statistical arbitrage fund, or even just developing HFT microstructure arbitrage algorithms, that have absolutely nothing to do with finance whatsoever.

financial modelling could mean looking at financial statements in Excel and doing some basic accounting maths in an area like M&A or credit research, or trying to fit a complex stochastic quantitative model to a particular pricing or volatility clustering problem.

the first step is understanding how it all ties together, who does what, banks, exchanges, brokers, funds, regulators, central banks, and the professions within them traders, market makers, structurers, strategists, economists, etc. it can take years..

then decide which career is right for you, acquire the specific skills if you don't have them, and be quick to land a job, to learn and adapt, the market is a constantly evolving place of survival.

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    $\begingroup$ I agree with your notion of a "label". Quant just means "very technical", so HFT and exotic options are both included even though there's no overlap between them. (This is also why there is no book for "quantitative finance", since that doesn't make any sense.) As a counter example, private equity and real estate are not particularly technical, so they don't get the label. $\endgroup$
    – chrisaycock
    Jun 26 '20 at 20:18
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    $\begingroup$ @chrisaycock I don't agree to define quant as 'very technical'. I don't call a technically superior programmer or IT specialist as a quant. Quant should have mathematical skills. And there are a lot of quantitative finance books. $\endgroup$
    – hbadger19042
    Jun 26 '20 at 21:35
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    $\begingroup$ @chrisaycock I don't see any difficult math in finance on average. Finance is an application field and you don't need to create anything new most of the time if you are not in the frontier. But it doesn't mean anyone can do the quant. $\endgroup$
    – hbadger19042
    Jun 27 '20 at 0:14
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    $\begingroup$ @Permian Sounds like you have a personal story to share. I look forward to reading it. $\endgroup$
    – chrisaycock
    Jun 27 '20 at 18:14
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    $\begingroup$ I think quant is just the generic term and then there are sub-categories. HFT probably has great programmers who cut milli-seconds using some not well known technique. stat arb desk could have econometrics or machine learning experts. sell side derivatives desk can have a math or physics-sde whiz. there are so many possibilities. $\endgroup$
    – mark leeds
    Jun 28 '20 at 0:22
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The late Mark Joshi wrote this rather famous advice on 'How to become a Quant'.

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    $\begingroup$ I've replaced the link to Mark Joshi's advice on the On Topic page with this question but wanted to preserve the resource. Hence, this link only answer. $\endgroup$
    – Bob Jansen ♦
    Jun 28 '20 at 12:47

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