Quant Interview Problem Book (1000+)

Digital Product

18Sales

A 400-page quant interview problem bank built for speed + correctness under pressure: derivations, method selection, and interview-style shortcuts (when they exist), with worked solutions throughout.

What you get

1000+ problems with worked solutions (problem-bank format; optimized for drilling)

Solutions written in a structured way (steps, sanity checks, common interview shortcuts)

Coverage that spans both quant math and quant dev / data engineering foundations

Topics covered (9 chapters)

Linear Algebra & Numerical Methods

Calculus, ODEs & PDEs

Probability Theory

Statistics & Econometrics

Stochastic Calculus

Financial Markets & Products

Stochastic Models by Asset Class

Programming & Data Engineering

Risk, Regulation & Model Governance

Who this is for

Aspiring Quant Analysts / Researchers / Strats / Risk Quants / Quant Devs

Candidates preparing for math-heavy interviews (whiteboard + take-home)

Anyone who wants a single drill bank instead of scattered PDFs/notes

How to use it (recommended)

Start with the chapters you’re weakest in; aim for 20–30 problems/week

Time yourself and write solutions as if in an interview (clean steps + final answer)

Re-do missed problems after 7 days (spaced repetition)

Coupon code

Use PROBLEMS10 for 10% off.

Regular disclaimer

Educational material only. No investment, legal, or tax advice. Results in interviews depend on individual preparation and circumstances—no guarantees are made. Any employer/affiliation mentioned is for identification only and does not imply endorsement.

What are people saying

Amazing content as usual!

Anonymous

Jan 2026

Good summary. Has done a lot of work to put this together. Think of it as a table of contents with lots of reminder notes. More like a roadmap. You still have to out in the hours.

Anonymous

Jan 2026

Good Starting point for someone to stitch the game between Products and tech and models and AI the underlying math, logic is always the game

Peter Joseph

Jan 2026

This content is aimed at a very specific audience: quants and technically strong practitioners who already know the mathematics and want to develop correct intuition, judgment, and interview-ready reasoning rather than memorizing formulas. What stands out is the consistent focus on practical failure modes such as correlation collapse, eigenvalue concentration, calibration instability, numerical blow-ups, and clear criteria for when PDE-based approaches stop being viable and Monte Carlo methods become necessary. These are insights that typically come from practitioner experience, not textbooks. One constructive suggestion I would offer is around structure. Given the depth and breadth of the material, it would be extremely helpful if Amit explicitly laid out a recommended reading order across the quant notes. As the creator, he is best positioned to guide learners on how to sequence the material for maximum clarity and impact.

ANUBHAB DE

Jan 2026

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