Careers
How quant careers actually work
The routes in, the roles you can hold, the strategies you can trade, and what each one pays.
What is a quant?
A quant is someone who uses mathematics, statistics and code to find and trade patterns in financial markets. The term covers several distinct jobs: researchers who build the models, traders who run them in live markets, developers who build the systems they run on, and analysts who price and risk-manage instruments.
Career guides
What is a quant?
A quant is a specialist who uses mathematics, statistics and code to find and trade patterns in financial markets. The term covers four distinct jobs: researchers who find signals, traders who run risk on them, developers who build the systems, and analysts who price instruments and model risk.
How do you become a quant?
Most quants enter through one of four routes: a quantitative PhD into research, a strong mathematics or engineering undergraduate degree into trading, a computer science background into quant development, or a financial mathematics masters into a bank quant-analyst seat. Interview preparation in probability and programming matters more than finance knowledge.
What is the difference between a quant researcher and a quant trader?
A quant researcher finds the signal; a quant trader runs risk on it. Researchers work on longer cycles with statistical depth and are hired mostly from PhD backgrounds. Traders work in real time with immediate feedback and are hired for speed of probabilistic reasoning. Trader pay is more volatile; senior researcher pay is often higher.
Do you need a PhD to become a quant?
No, but it depends on the role. Quant research at systematic funds is overwhelmingly PhD-hired, so a doctorate is close to a requirement there. Quant trading, quant development and low-latency engineering are not PhD-gated, and many of the highest-paid people in those seats hold only an undergraduate degree.
Can a software engineer move into quant finance?
Yes — quant development is the most accessible entry point into the industry for experienced software engineers, and firms hire directly from large technology companies. The realistic target is a quant developer or low-latency engineering seat rather than a research role, and total compensation frequently exceeds equivalent big-technology packages.
Roles
Quant Researcher
Signal discovery and alpha research
Quant Trader
Running risk on systematic strategies
Quant Developer
The engineering layer beneath the strategy
Quant Analyst
Pricing, risk and model validation
HFT / Low-Latency Engineer
Nanoseconds as a competitive edge
Systematic Portfolio Manager
Owning a book and a payout formula
Strategies
High-frequency trading
High-frequency trading captures very short-lived pricing edges by being faster than competitors to observe and act. The edge is largely engineering: network path, kernel bypass, and increasingly FPGA implementation of the decision hot path.
Hires most in: Chicago · Amsterdam · New York
Market making
Market makers quote continuous two-sided prices and earn the spread while managing inventory risk. Options market making is the largest and most quantitative variant, requiring volatility modelling alongside fast systems.
Hires most in: Amsterdam · Chicago · Hong Kong · Singapore
Statistical arbitrage
Statistical arbitrage trades large baskets of related instruments on mean-reversion and relative-value relationships identified statistically. It is the classic quant research discipline and the deepest employer of doctoral researchers.
Hires most in: New York · London · Hong Kong
Systematic macro
Systematic macro takes rules-based positions across currencies, rates, commodities and equity indices based on macroeconomic and trend signals. Horizons are long, capacity is high, and London is the global centre.
Hires most in: London · New York · Singapore
Machine-learning alpha
Machine-learning driven strategies use modern statistical learning and alternative data to find non-linear structure in markets. It is the fastest-growing research discipline and competes directly with AI labs for talent.
Hires most in: New York · San Francisco · London
The Quant Career Graph →
Every common route into quant, from physics PhD to portfolio manager, mapped step by step.
Methodology
Figures are expressed as annual total compensation (base salary plus expected performance bonus) in the reference market's local currency, converted from a US dollar base. They describe typical market ranges rather than any individual offer, and exclude sign-on payments, deferred equity and carried interest. Portfolio-manager figures reflect formulaic profit-share arrangements and are therefore far more dispersed than any other role.
KnowQaunt 2026.1 · Updated September 2026
These are indicative ranges pending first-party verification. They will be replaced by verified submissions as the Quant Salary Index dataset builds.