A quant is someone who uses mathematics, statistics and computation to make decisions in financial markets. Instead of forming a view and trading it, a quant builds a model, tests it against data, and lets the model decide.
The word covers several jobs that share a method but differ in what they produce.
The main types
Quant researchers look for patterns in data that predict returns — signals, factors, anomalies — and turn them into strategies. Quant traders run those strategies live and manage their execution. Quant developers build the infrastructure that connects the two. Risk quants model what could go wrong and how much.
At large firms these are distinct roles. At small ones the same person does all four.
What a quant actually does all day
Cleans data. Most of the job is making sure the inputs are correct, because a model trained on flawed data produces a confident wrong answer. Then: forming hypotheses, testing them, discarding most, refining the survivors, and watching for the moment a working strategy stops working.
How quants differ from discretionary traders
A discretionary trader forms a judgement and acts on it. The edge lives in the person. A quant encodes the judgement into rules that can be tested, measured and run without them. The edge lives in the process.
Neither is inherently better. Quants are more consistent and less adaptable; discretionary traders are the reverse.
Quants in crypto
The same methods, applied to a market with continuous trading, extreme volatility, and public on-chain data that has no equivalent in traditional finance. Every position on a fully on-chain venue is visible, which gives crypto quants a dataset traditional quants would pay anything for.