Meta Statistics & Math interview questions at Meta emphasize clear statistical judgment applied to product problems rather than rote formula recall. Interviewers typically probe experimental design, hypothesis testing, confidence intervals, power and sample-size thinking, probability and distribution intuition, and practical trade-offs at scale. What’s distinctive is the expectation that you tie statistical conclusions to product impact: show how uncertainty, effect size, seasonality, and clustering would affect a recommendation, and how you’d instrument guardrails to prevent harm. Expect a mix of brainteasers, short analytical problems, and open-ended experiment or metric-diagnosis cases that require both math and product sense. For interview preparation, focus on fundamentals (CLT, t-tests, p-values vs effect size, Bayes basics) and practice translating results into decisions. Work timed problems that include A/B design, power calculations, and conditional probability, and rehearse explaining assumptions and limitations concisely. Use mock interviews to sharpen verbalization of uncertainty and trade-offs, and prepare examples where you diagnosed noisy metrics or redesigned experiments—Meta favors candidates who demonstrate sound statistics and pragmatic product thinking.