Quant interviews — at Jane Street, Citadel Securities, Two Sigma, Optiver, IMC, SIG, DE Shaw, HRT, and the rest of the prop desks — test a different mix of skills than software engineering interviews. The bar is fluency in probability and mental math, plus the ability to reason cleanly under time pressure on problems you've never seen. Most general-purpose interview prep doesn't cover this well.
This page is the honest taxonomy of what actually works for quant trading and quant research interview prep — books, brainteaser banks, mental-math drills, and mock interview platforms — at each stage of the prep cycle.
How quant interviews differ from software engineering interviews
Software engineering interviews test: algorithm fluency, system design judgment, code quality, communication.
Quant trading interviews test: mental math under pressure, probability fluency, market-making logic, expected-value reasoning, brainteasers, occasionally programming.
Quant research interviews test: statistics, signal design, time-series intuition, hypothesis testing, occasionally programming and ML.
The skills compound differently. A strong software engineer who's never drilled mental math can be at the bar in the rest of a quant interview but get knocked out by the first dot-product-of-two-7-digit-numbers question. Conversely, a strong math student with no coding background can sail through the math sections and stall when asked to write a working Python class.
The honest list
Books
A Practical Guide to Quantitative Finance Interviews (Xinfeng Zhou)
Best for: probability, brainteasers, basic stochastic calculus. The most widely used quant interview prep book. Comprehensive coverage of probability, brainteasers, calculus, stochastic processes, and option pricing. Most quant candidates work through this end-to-end.
Where it falls short. Some sections are dated; option pricing is more depth than most trading interviews need. For trading-specific roles, skim the stoch calc chapters and focus on probability and brainteasers.
Heard on the Street (Timothy Crack)
Best for: brainteasers and finance interview classics. A more narrative approach — interview-style problem walkthroughs across quant, banking, and trading. Older but still relevant; many of the brainteasers are direct lifts of what firms ask in 2026.
Where it falls short. Less rigorous than Zhou; some of the problems are repeated across quant interviews to the point that nailing the book solution doesn't differentiate you.
Fifty Challenging Problems in Probability (Frederick Mosteller)
Best for: building probability intuition through hard problems. A classic — short, dense, and the problems are exactly the kind that show up in interviews. If you can solve all 50 cleanly, your probability is in good shape.
Pricing. Cheap, ~$10 paperback or free digital.
Brainteaser banks
InterviewDen Quant Trading Brainteasers
Best for: drillable Q&A with sample solutions and follow-ups. A bank of 18 representative quant trading brainteasers — probability puzzles, market-making setups, expected-value problems — with clean derivations and the follow-ups firms actually ask. Browse the bank.
Pricing. Free.
Glassdoor / Wall Street Oasis / r/quant
Best for: company-specific recon. Past candidates report what they got asked. Useful for confirming which firms over-use which question types (Optiver = mental math, Jane Street = probability + market making, SIG = trading games + brainteasers, Citadel Securities = mixed).
Where it falls short. No solutions, no scoring, no practice — just intel. Use it to find what to drill, not as a place to drill.
Mental math drills
Zetamac (arithmetic.zetamac.com)
Best for: fast, drillable mental math. Free web-based mental math timer. Configurable to match what specific firms test (Optiver runs 8-minute Zetamac-style tests; SIG uses similar formats). The default 2-minute test is what most quant candidates use as a daily warm-up.
Pricing. Free.
Tradermath / Optiver Math App
Best for: trading-specific mental math drills. Some firms publish their own mental math apps (Optiver has historically had one). Drills include arithmetic, fractions, percentages, sequences. Worth using if you're targeting a specific firm.
Pricing. Free.
Mock interview platforms
InterviewDen (Quant tracks)
Best for: full mock interviews with live AI follow-ups across quant trading and quant research. Voice-driven AI interviewer with dedicated tracks for quant trading (mental math, market making, brainteasers) and quant research (probability, statistics, signal design). Free, unlimited, on-demand.
Where it falls short. AI grading on probability problems is consistent but won't fully replicate the variance of a Jane Street trading interviewer who improvises a follow-up that takes the problem in a totally new direction. Use as your primary practice, layer in human practice late-stage.
Pricing. Free.
interviewing.io
Best for: paid coding mocks specifically. interviewing.io's interviewer pool includes some quant engineers, but the coverage is thin — most sessions are general software engineering, not quant-specific. For coding rounds at quant firms (which exist and matter), it's useful.
Pricing. $225–$450 per session.
Wall Street Oasis Mock Interview Marketplace
Best for: paid mocks with finance / quant industry coaches. Variable quality; some genuinely strong coaches with prop trading or quant research backgrounds, alongside generic interview coaches. Vet the coach before paying.
Pricing. Variable, ~$100–$300 per session.
For quant research specifically
A First Course in Probability (Sheldon Ross)
Best for: probability foundations. The textbook reference. If your probability is shaky, this rebuilds it from first principles. Overkill if you're already comfortable.
All of Statistics (Larry Wasserman)
Best for: statistics review at the right level. Concise, broad, exactly the level quant research interviews test. Better than working through a heavier statistics text if you're prepping in weeks not months.
Time Series Analysis (Hamilton)
Best for: deep time-series for research roles. Reference-grade; you don't need to read it cover-to-cover but you should have it on the desk during prep.
What to actually use, by stage
Stage 1: Mental math (weeks 8+ out, daily)
Primary tool: Zetamac, daily. Goal: 50+ problems in 2 minutes by the end of the week. 80+ if you're targeting Optiver / IMC / SIG. The bar is muscle memory — you should be able to multiply two 2-digit numbers without thinking about it.
This is the cheapest, highest-leverage skill to build. Five minutes a day for 8 weeks = 4–5 hours of compounded practice. You will find that everything else gets easier when the math is reflexive.
Stage 2: Probability fluency (weeks 8–4 out)
Primary: Quant Practical Guide (Zhou) chapters 4–7 + 50 Challenging Problems in Probability. Secondary: InterviewDen Quant Trading Brainteasers.
Goal: Conditional probability, Bayes, expected value, and basic combinatorics at the level where you can solve a typical interview problem in 90 seconds. If you're stuck above 3 minutes per problem, more solo work first.
Stage 3: Mock interviews and follow-ups (weeks 4–1 out)
Primary: InterviewDen quant tracks, daily mocks. Mix quant trading and quant research by what you're interviewing for. Secondary: Paid mock if you have one to spend on (interviewing.io for coding; WSO marketplace for full quant).
Goal: Drill the conversation around the math. The actual EV calculation is no longer the bottleneck — the bottleneck is staying composed when the interviewer pushes "what if I changed this assumption?" and you have to redo the calculation in 30 seconds.
Stage 4: Final week
Light reps only. Re-read your strongest brainteasers. Sleep. The work was already done.
Firm-by-firm prep notes
Jane Street
Heaviest emphasis: probability, brainteasers, market making, occasional programming. Format: 4–5 rounds. Probability and brainteaser rounds early; trading game and behavioral late. Drill emphasis: Bayesian reasoning, conditional probability, market-making logic. Use InterviewDen quant trading mocks for the conversation practice.
Citadel Securities
Heaviest emphasis: quantitative reasoning + programming. The trading desk hires hybrids who can write production code. Format: Mixed — probability, mental math, coding, behavioral. Drill emphasis: Both quant and software engineering tracks. Don't let coding atrophy.
Two Sigma
Heaviest emphasis (for QR): statistics, ML, time-series, signal design. Heaviest emphasis (for SWE): standard software engineering with quant-flavored problems. Drill emphasis: All of Statistics + ML basics for QR roles; standard SWE prep for engineering roles.
Optiver
Heaviest emphasis: mental math (Zetamac-style), trading games, market making. Format: Math test → trading game → final-round behavioral. Drill emphasis: Zetamac at 80+ score consistently. Drill market-making logic and EV calculations under time pressure.
IMC
Heaviest emphasis: market-making, mental math, probability. Drill emphasis: Same as Optiver, with more EV reasoning.
SIG
Heaviest emphasis: market making, brainteasers, trading games. Heavy poker influence in their style. Drill emphasis: Brainteasers + market-making conversations + game-theory intuition.
DE Shaw / HRT
Heaviest emphasis: quantitative depth, often role-specific (research roles much heavier on stats; software roles more standard). Drill emphasis: depends entirely on role. Read the JD carefully.
FAQ
How long should I prep for a quant interview?
Realistic minimum is 8 weeks for a serious candidate; 12 weeks if your math fundamentals are rusty. Less than 4 weeks and most candidates can't compress probability fluency + mental math + behavioral drills into the timeline.
Do I need to be good at coding for quant interviews?
For trading roles: usually no, beyond basic Python (some firms test FizzBuzz-level). For software engineering at quant firms: yes, full SWE bar. For quant research: usually some Python and basic ML/stats coding.
How important is mental math really?
At Optiver, IMC, and SIG: critical. You can fail the round on math alone. At Jane Street, Citadel, Two Sigma: less central but still graded — being slow on arithmetic looks bad even when the underlying logic is correct.
Can I actually learn this skill in 8 weeks if I haven't done quantitative work since college?
Yes, but it requires daily commitment. The candidates who land at top quant firms with non-quant backgrounds typically did 1–2 hours of math per day for 8+ weeks plus 20–30 mock interviews. The math is teachable; the discipline is the binding constraint.
What's the worst mistake quant candidates make?
Skipping mock interviews because they think "I just need to solve harder problems." The bottleneck for most candidates above the math bar is the conversation — staying composed, articulating reasoning, handling follow-ups. That's a separate skill from problem-solving and it only develops with reps.