This is the heart of quant interviews. If you fail probability, you fail the interview.

Quantitative finance has become one of the most coveted yet challenging fields to break into. Whether you are aiming for a role at a top-tier hedge fund (Citadel, D.E. Shaw), an investment bank (Goldman Sachs, Morgan Stanley), or a proprietary trading firm (Jane Street, Optiver), the quant interview process is notoriously rigorous. It is a multi-layered gauntlet designed to test not just your mathematical memory, but your stochastic intuition, coding fluency, and mental arithmetic under pressure.

How do you find the expected time to absorption in a chain with two absorbing states?

Give the geometric and algebraic definitions of eigenvalues. How are they used in Principal Component Analysis (PCA)?

You have a coin with an unknown probability

Write a pseudocode snippet to forward-fill missing tick data in a high-frequency time series data frame.

Why are GARCH models used to model financial asset returns instead of standard autoregressive time-series models?

Why do quantitative researchers train models on log returns rather than raw nominal asset prices?