Airbnb Analytics & Experimentation interview questions focus on rigorous, product-aware measurement for a two-sided marketplace. Interviewers typically evaluate your ability to define and instrument clean metrics, design randomized experiments and interleaving tests for ranking, reason about statistical power and variance reduction, and translate results into product trade-offs. Expect technical screens with SQL and Python problem-solving, a dedicated experimentation/statistics round that probes hypothesis design and guardrail metrics, and product-analytics conversations that stress causal thinking and business impact. For interview preparation, concentrate on three areas: practical tooling and technical fluency (SQL window functions, joins, CTEs, time-series/sessionization, and Python for data munging), experimental design and inference (power calculations, covariate adjustment, sequential testing pitfalls, attribution), and product sense framed by marketplace dynamics (supply-demand effects, long-tail metrics, and guardrails). Practice explaining trade-offs clearly and walk through end-to-end problem solving: define the metric, show how you would compute it, design the experiment, and describe how results would change product decisions. Mock interviews and worked A/B post-mortems are especially helpful.