5 Misconceptions About Becoming a Quant Trader

October 23, 2021

5 Misconceptions

You know that I don't like wasting time, so let's get into it.

Misconception #1: You need a STEM degree

This is probably the most pronounced misconception out there. That being that you need a degree in either science, technology, engineering, or math to become a quantitative trader. While it is true that most quantitative traders do come from STEM backgrounds, that does not mean that it's a hard requirement. In fact, I know a quantitative trader that holds a degree in music. While many firms still hire based on degree qualifications (moreso in quantitative trading than in other industries), there is a strong push by a contingent of firms in the industry to employ more progressive hiring strategies. By this I mean that your ability to get your foot in the door at these firms are no longer dependent on the school you went to, or the degree you possess, but is dependent on your ability to pass a minimum technical bar. This technical bar often manifests itself as a quasi-IQ test. The exact form of the assessment - whether the assessment is a take-home or not, for instance - is beyond the question.

Above and beyond understanding that quantitative trading is trending towards more progressive hiring practices, one should keep in mind that a diligent in-house recruiter with years of experience is more than capable of seeing one's education section on their resume. By this I mean that a talented recruiter is able to spot nuggets of information on your resume that would signal to him/her that, while you don't come from a STEM background, you are a candidate capable of succeeding in the role. If you find yourself in this STEM-less category, it is up to you to craft your resume in a way that communicates the value you'll bring as a prospective quantitative trader. As a shameless plug, I do provide resume review services that help you market yourself to prospective employers.

Misconception #2: You need to learn to code

I hear this one a lot, so let's talk about it. No, you do not need to learn to code. Okay, I talked about it, let's move on. Just kidding, let's dive deeper.

Some companies will include something along the lines of 'we hope you can code' in their job requirements section. Firstly, always remember that the job requirements sectionis a wishlist. In other words, if you check all those boxes you are the ideal candidate; but, don't let that discourage you, as most companies hire candidates that don't check every box. In fact, I received an offer from Soundhoud which stated that the candidate requires 2-3 years of programming experience (at the time, I had 0). Secondly, you don't need to learn to code, at least not yet. I have no doubt that in twenty years, quantitative traders will be required to code (or at least be required to understand code). Nowadays, being a quantitative trader that knows how to code is a nice-to-have, as opposed to being a must-have. In other words, being a quantitative trader that can code is an advantage that will benefit you by both allowing you to speak the language that quantitative developers speak and better acclimate yourself to the data-driven approach of quantitative trading. That may mean that, on the job, you utilise your coding skills to query information from a data lake and perform an analysis of interest on the fly.

Taken from Optiver's career section. Knowing how to code as a quantitative trader candidate is a plus, not a requirement.

Misconception #3: You need to be a machine learning expert

Just stop. Yes, I said it - stop. Put down down PyTorch. Put down Tensorflow. You won't be using it, especially as a quantitative trader. Yes, some firms do employ machine learning in their trading practices; but, if they choose to do so, they'll hire machine learning specialists who will sit in a division between quantitative research and quantitative trading (they'll most likely be quantitative research-adjacent). In other words, you're not going to be coding-up neural networks. I know, boo-hoo, you're sad about it. Well, get over it. This misconception is somewhat similar to the its predecessor, but is still worth mentioning given the prevelance of would-be quantitative traders spending most of their time learning PyTorch and not enough time reading Sheldon Natenberg's Option Volatility & Pricing. As a candidate, your time is better spent brushing up on your theory.

Misconception #4: As a quantitative trader, you will need to adopt a dog-eat-dog mentality

Amongst firms, the world of quantitative trading is dog-eat-dog; but, within your own organization, the mentality you adopt must not be rooted in the ideals of kill-or-be-killed. A quantitative trading firm is a well-oiled machine that needs to iterate on new ideas quickly if it's going to stand any chance against its competitors. In light of this, it is your responsibility to harmoniously co-operate with your fellow quantitative traders. Yes, this means that the person to your left, and the person to your right, are not your enemies - your teammates are your friends! Quantitative traders that see their peers as their enemies don't go very far; remember, if you're on the same desk, you're trading the same book!

The way I like to describe intra-firm dynamics is dog-eat-self. By this I mean that your manager will benchmark you against an index of average performance. If your performance is average, you stay. If it's more than average, you stay. If it's less than average, you're gone. In all these three scenarios, your manager is comparing you to an agreed upon set of metrics previously determined by HR. The success or failure of your teammates do not factor into this equation. In this sense, the only person that can eat you is yourself; hence, the dog-eat-self mantra. That means that you are ultimately responsible for your own ascension in the organization, not the guy or girl beside you.

Misconception #5: You can't transition into quantitative trading after graduation

A lot of people ask me whether or not they can break into quantitative trading after having spent X years in industry Y. Their questions often look something like this:

CJ, I have a degree in computational physics, can I make it into quantitative trading?
CJ, I have a degree in underwater basket weaving, can I make it into quantitative trading?
CJ, my dog ate my degree, can I make it into quantitative trading?

Yes, no, and maybe. Well, I don't really know. In any case, what I want to address is that it doesn't matter what what you currently do, as long as you are qualified for the position. What people often forget about quantitative trading as an industry is that it doesn't matter how you look or where you come from. As long as you can perform, you can have three arms and four legs, nobody cares. I've worked with and spoken to people in the space that have transitioned mid-way through unrelated careers (for example, at age 32) into the industry.

Now, I don't want to imbue in you any unrealistic expectations. If you're 72, it's not very likely that you will be selected as a candidate to fill a Junior Quantitative Trader position, despite having the requisite skillset. This is because there are other considerations in hiring for a junior role, like your ability to grow (and stay with) your employer. And, at age 72, you're not very likely to spend the next ten years developing in your role to becoming a senior quantitative trader and eventually running a desk. What I'm getting at here is that age (in non-fringe circumstances) is not an impediment.

Conclusion

Hopefully you found the debunking of these five misconceptions helpful. As I get sent more questions, I'm sure I'll be addressing even more misconceptions around the industry related to hiring, culture, work-life balance, and more.

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