— GUIDE —
WHAT IS QUANT FINANCE?
Quant finance is what happens when people use math, code, and data to make decisions in markets. Here is who does that work, where they do it, and what the job actually looks like.
UPDATED 2026-09-08 · 5 MIN READ · BY THE VARIANCE TEAM
The word covers several different jobs, so any definition broad enough to fit all of them ends up saying very little. It is easier to look at what the work involves and where it happens.
The short version
Quant finance is what happens when people use math, code, and data to make better decisions in markets. Sometimes that means figuring out what a complex contract is worth. Sometimes it means finding a pattern in years of price data. Sometimes it means making sure the software does not fall over when markets get wild.
The label sounds more mysterious than it is. It is not one job, and it is not a room full of people day trading from six monitors.
Where quants actually work
The firm type shapes the work more than the job title does. The same person can be pricing options on a one-second horizon at one shop and testing a signal over ten years of data at another.
| Firm type | What the work tends to look like |
|---|---|
| Market makers | Quoting two-sided prices continuously and managing the risk of whatever gets traded against you. Fast feedback, short horizons. |
| Proprietary trading firms | Trading the firm's own capital on strategies the team builds. Often heavy on speed, infrastructure, and automation. |
| Hedge funds | Researching signals that hold up over longer horizons, then sizing positions across a portfolio. |
| Banks | Pricing and hedging derivatives for clients, plus risk and model validation work. More structured, more regulated. |
So what do quants actually do?
A market maker might quote a price for an option and manage the risk when someone trades with them. A researcher might test whether a data signal survives contact with reality. A developer might make a trading system fast enough to use the model in the first place. They work on different problems, but they all care about evidence over hunches.
The tools are less exotic than the reputation suggests. Probability, statistics, and linear algebra come up constantly. Python does a lot of the analysis; C++ shows up where latency matters. A surprising amount of the job is data cleaning, checking whether a result is real, and explaining a decision to someone who will push back on it.
How it differs from discretionary trading
A discretionary trader makes a call based on judgment about a specific situation. A quant tries to define the decision rule in advance, then test whether it holds up across many situations. Both can be right or wrong. The difference is where the reasoning lives: in the moment, or in something written down that can be measured later.
That is also why the interviews look the way they do. If the job is about defensible reasoning under time pressure, the screen tends to test exactly that. The firm-format guide covers how different firm types weight speed against depth.
Who tends to enjoy it
You do not need to have been obsessed with the stock market since age twelve. It helps more if you like asking why something works, noticing when an answer feels off, and revisiting an idea after the data disagrees with you.
If that sounds like your kind of problem, the next question is which seat you want. Start with the trader, researcher, and developer comparison.