The Old Exchange of Amsterdam (1670), Job Adriaenszoon Berckheyde

Flirting with Quant

The fluorescent lights of the Sloan study room flickered.

They buzzed, casting an eerie glow over the sea of notebooks and energy drinks strewn across the desk. It was liminal 3AM July night (morning?), and I found myself staring blankly at yet another probability problem. It was taunting me. It mocked my efforts. This scene had become too familiar over the months prior. Why? Because I wanted to be a quant.

Quant was an obsession for me. My older friends, and the people I followed online, already worked or secured coveted positions at these quant firms. I wanted in, too. I heard about all of the perks: the free food, unlimited Diet Dr. Pepper, gym, housing, baseball games, and merch. I drooled over the salaries and that sweet, sweet sign-on bonus. Seeing the success of my older friends and liking the thought of playing poker all day for a summer (oversimplification) motivated me to get a quant job.

But it wasn't just about that juicy sign-on bonus and the prestige of saying I worked in finance. Deep down, a part of me hoped that landing a quant job would finally silence the nagging voice of inadequacy that had taken residence in my head last year. The friend group that I was in last year was toxic. All of them were very intelligent and overachieving. The problem was that they were snobby about it. It didn't support a lot of confidence in myself and made me feel like an impostor. A fraud even. Quant, in that context, became a lifeline. A chance to prove my worth.

So I dove in, head first and eyes wide open. Nights blurred into days as I scoured every resource I could find—Glassdoor, Reddit, 3point1acres, WallStreetOasis, Blind—hunting for the secret formula to get into quant. After months of hard work, some successes, and some failures, here's what I found about preparing for and getting into quant:

First off, I don't know if I am qualified or not to give advice. My background is atypical. I have zero competitive math background, have never done the Putnam, and all of my prior experience is in software engineering. These are just my thoughts and how I prepared. Please take everything with a grain of salt and take this guide more as a list of suggestions and possible resources to use to prepare for quant. I also will talk about why I personally thought quant wasn't right for me after doing all of this.

To begin, a lot of online resources and prep books are stupid, bloated, or irrelevant. There are only a handful of resources that actually helped me. Also, preparing for quant and SWE will get you nowhere. This was probably my biggest mistake. I thought I could do both. I couldn't, and you probably can't either. The mental models you have when preparing for interviews in quant vs. interviews in SWE, are very different, and it's best to refine one at the expense of the other.

Poker

Learn poker and play lots of it. Lots of quant questions, at their core, are similar to poker. Many quant questions ask if or how much money you should put into a game given some information. A lot of times this game is a card game like poker. The pace of quant interviews is too fast for you to really sit down and think about exact pot odds or probabilities.

You have to build up your intuition and reaction time to respond and get "hunches" or "gut feelings" that you think are correct. This can most effectively be built up by playing lots of poker and practicing poker theory while playing quick games against an opponent. Some resources and terms that helped me build my poker intuition were:

Puzzles

In addition to building poker intuition, building puzzle intuition helped a lot. Brainteasers aren't really asked a lot anymore in quant questions, although they do pop up sometimes (based on other friends' accounts). You can kind of think of solving puzzles as a more passive study method.

When you are bored of actually practicing quant questions, just do some of these puzzles or watch some of these videos to still build up your intuition. Although you won't usually be asked these kinds of brainteasers, thinking about the solutions, even if they are unexpected or counterintuitive, can allow you to apply those techniques on interview problems. Some resources and videos that helped me build my puzzle intuition were:


Studying for quant is NOT like studying for SWE. It involves more intuition and much more practice than memorizing algorithms and mapping LeetCode solutions onto a given question. There are four main areas that get tested in quant: arithmetic, probability, applied trading questions, and market knowledge. If you build up your intuition and skills in these areas in this order, then you should be well-prepared to do quant interviews

Arithmetic

For arithmetic, you need to know how to do harder mental arithmetic at high speeds. This could be for a specific arithmetic test they have you do, or for making calculations or approximations for certain values in an interview. You should not move on to probability until you are comfortable with fast mental arithmetic. Some resources that helped me with my mental arithmetic are:

Probability

For probability, you need to know probability theory first. If you have taken a discrete math class before, you probably already know enough, but reviewing some of it with either the MIT Discrete Math OCW course or a textbook is a good idea. You should focus on card problems and dice problems. My friends and I encountered tons of dice problems, and the card problems aren't hard if you already built up your poker intuition. Here are some resources that you should go through to build up your probability intuition:

Trading Questions

For the applied trading questions, you should practice them until you can instantly think of an approach or trick to solve the problem. This is like the most "LeetCode" portion of interview prep, so memorizing and understanding solutions should be sufficient. Here are some resources that helped me prep:

Market Knowledge

For market knowledge, I didn't have a lot of trouble because I was already familiar with economics and finance. However, if you have no experience in these areas, definitely learn some trading-centric terms and concepts. You don't have to understand the deep intricacies of the market, but you should know when to apply finance-influenced common sense to a trading scenario. Akuna Capital has a good course that covers enough high level understanding of the market and exchanges. You can also look on Investopedia for what specific terms like "market maker" mean.

For preparing for interviews, I made friends who had interviewed or worked at those places to give me mock interviews. When they weren't available, I did a back and forth with ChatGPT. I also looked at Glassdoor and Blind for what trading interviews at those firms looked like. I mainly applied to the firms that were sponsors of MITIT along with a few smaller firms and even some firms that I later found out were crypto-centric. Here is how I would rank the quant firms based on my experience:

Sponsors MITIT + They Love Me: Hudson River Trading, Jane Street, Jump Trading

Sponsors MITIT + They Don't Dislike Me: Five Rings, Citadel, Tower Research Capital

Doesn't Sponsor MITIT + OK: Akuna, Arrowstreet, Capula, Chicago Trading Company, DE Shaw, DRW, Flow Traders, IMC, Optiver, Old Mission Capital, Radix, SIG, Two Sigma

Doesn't Sponsor MITIT + Huh: Acadian, AQR, Balyasny, Belvedere, Bridgewater, Cubist, DV Trading, Garda, PDT Partners, Peak6, Schonfeld, Wolverine Trading

A Realization

However, after months of intense practice and lots of awkward or triumphant interviews, I started to feel my frosted quant dream cookies crumble. The more I interviewed and learned more about the kind of work you do as a quant, the more I realized I actually didn't like it. The more I practiced probability and thought about poker, the more I yearned for the creative, hands-on problem solving of SWE. Quant trading and research, both of which I had convinced myself I would grow to love, never actually stuck with me.

As I reflected on my past experiences—the UROPs that had always gravitated towards software engineering, even when disguised as research—a weight began to lift from my shoulders. I realized that in my desperate quest for validation, I had nearly abandoned the field that truly ignited my passion. The irony wasn't lost on me. In trying to prove my worth, I had almost lost sight of what made me truly valuable in the first place. I was treating SWE like a fallback option; it was where my strengths and interests truly aligned. I abandoned a good friend just to try and hang out with the popular kids. I was Cady from Mean Girls.

So here I stand, at the end of a journey I never expected to take. The quant preparation materials I amassed - the probability guides, the market intuition resources, the arithmetic drills - they're still valuable tools that have sharpened my technical skills. But they're not a blueprint for my future.

To the younger students who might be interested in quant, I offer this; There's immense value in pushing your boundaries and exploring new fields. Any new skill you gain and the self-knowledge you acquire is never wasted. However, don't let the allure of prestige or the fear of inadequacy drown out your true passions.

I was not passionate about quant. As much as I wanted to be a trader, I realized I wouldn't enjoy the actual work involved. You shouldn't do something you wouldn't actually enjoy, right? If you don't know if you want to do quant and you don't have the probability intuition or arithmetic speed already, then I suggest you do something you are truly passionate about. If you love probability and numbers and poker and would love to do research and statistics, then definitely do quant.

I have a new appreciation for SWE, and a near-addiction to coding now. Trading or research at a quant firm might not be my destination, but building the software those traders use at that firm might be. Ultimately, trying and half-succeeding at getting into quant made me more secure in being a SWE. My path forward is clearer, not because it's easier, but because it's mine.