Jane Street Interview Loop
Jane Street is one of the most selective quantitative trading firms in the world. Interviews are heavy on probability, expected value calculations, and market-making scenarios — all conducted interactively with interviewers who push back on reasoning. The coding screen uses functional programming (typically OCaml). The Culture Fit round probes intellectual honesty and whether you thrive in Jane Street's collaborative, curiosity-driven trading environment.
Start your Jane Street loopThe 4-round process
Background and quantitative trading context
Probability puzzles, expected value, and market-making scenarios
OCaml or functional programming — clarity and correctness
Intellectual honesty, collaborative trading culture, and curiosity
Common questions about Jane Street interviews
What math topics come up in Jane Street interviews?
Jane Street's trading interviews cover: expected value and probability trees, combinatorics and counting problems, conditional probability (Monty Hall-style), market-making bid/ask reasoning, Bayesian updating, and geometric probability. Problems are posed interactively — the interviewer gives feedback and asks you to refine your reasoning as new information arrives. Reasoning out loud is as important as the answer.
Why does Jane Street use OCaml for coding interviews?
Jane Street uses OCaml as its primary programming language for production trading systems because of its strong type system, performance, and functional programming properties. Coding interviews use OCaml to assess functional thinking — pattern matching, recursion, immutable data structures, and type-safe code. Some roles allow other functional languages, but OCaml proficiency is strongly advantageous.
How many rounds does Jane Street interview have?
Jane Street's process typically runs 4 rounds: Recruiter Screen → Mental Math & Trading puzzles → Coding Screen → Culture Fit. The onsite is typically a full day with multiple back-to-back interviews. Jane Street is extremely selective — acceptance rates are very low. Preparation in probability, expected value, and functional programming is essential.
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