Whom do HFT Firms Hire?
by Alessandro Ishak
High-frequency trading firms (covered in a previous blog) are built around small, highly specialised teams. Despite the technical nature of the work, the internal structure is relatively simple and flat:
Traders oversee live trading systems. They monitor performance, manage risk limits, and decide when a strategy should be adjusted or shut down. They do not manually place trades. In the UK, entry-level trader compensation is typically £150k–£250k total. In the US, this is often $250k–$400k, with strong performers earning significantly more.
Researchers design the mathematical and statistical models that drive pricing and risk decisions. Many come from maths or physics backgrounds. UK researchers often earn £120k–£220k early on, while US compensation commonly ranges from $200k–$350k.
Engineers build the infrastructure that makes everything work, from low-latency systems to simulation platforms. Their pay is comparable to traders and researchers. In the UK, £120k–£200k is common early career, while in the US $200k–$350k is typical.
Pay is highly performance-linked. Exceptional contributors can earn multiples of these figures, but results matter far more than titles.
High frequency trading firms hire primarily for raw problem solving ability rather than traditional finance experience. Common university backgrounds include mathematics, physics, computer science, engineering, and occasionally economics. The specific university matters less than demonstrated ability, though many hires come from strong quantitative programmes.
Grades do matter, but not in isolation. Firms typically expect very strong academic performance, often top percentiles, but they care more about how candidates think than perfect transcripts. Interviews are designed to test reasoning under pressure rather than knowledge.
Competitions carry significant weight. Maths Olympiads, coding competitions, trading games, poker style probability challenges, and algorithmic contests are all strong signals because they reveal real skill. These often matter more than internships or CV polish.
Average incoming hires usually have little to no finance experience. Many join straight from university or after short research or tech roles. What matters most is clarity of thought, comfort with uncertainty, and the ability to learn quickly.
Why do Mathematicians and Physicists dominate in HFTs?
High frequency trading firms are not looking for people who can memorise finance theory or predict market headlines. They are looking for people who can reason clearly under uncertainty. Financial markets at this level behave like complex systems, with randomness, feedback loops, and noisy data.
Mathematicians and physicists are trained to work in exactly this environment. They are comfortable modelling probability, analysing distributions, and separating signal from noise. They also tend to think in first principles rather than relying on intuition or rules of thumb.
Most firms teach the necessary market knowledge internally. What cannot be taught easily is the ability to think precisely, test assumptions rigorously, and remain disciplined when outcomes are uncertain. These skills are why maths and physics graduates are so heavily represented.
What a “trader” means in HFT vs Banks
At banks, traders usually take discretionary risk. They manage a book, form views on markets, execute trades, and are judged partly on judgment and intuition. Client flow and human decision-making play a central role.
In high frequency trading, the trader does not manually trade. Algorithms execute all orders. The trader’s role is to supervise these systems, manage risk limits, monitor live performance, and intervene only when something behaves unexpectedly. The focus is on control, consistency, and risk management rather than prediction. In practice, an HFT trader is closer to a systems operator than a traditional market speculator.
