Meta Behavioral & Leadership Interview Questions
Practice 1,166 real Meta interview questions for 2026. Covers top categories — Coding & Algorithms, Analytics & Experimentation, Data Manipulation (SQL/Python), Behavioral & Leadership, and System Design — across Software Engineer, Data Scientist, Machine Learning Engineer, Data Engineer, and Product Manager roles. Real questions from actual interviews with detailed solutions. Expect a software-engineering-heavy loop: timed algorithmic coding (trees, arrays, graph/maze problems, delimiter/CSV parsing), system-design prompts like leaderboards, flight search and online-judge architectures, and an increasingly common AI-assisted coding round that mirrors real workflows. Data Scientist rounds emphasize product analytics and experimentation—designing tests, diagnosing spend drops and bots, evaluating unconnected content, and writing SQL for multi-account, seller, and vehicle metrics. Machine Learning Engineer questions skew toward recommender and ranking work (place and friend recommendation, sparse-matrix ops, linear-regression derivations, newsfeed dislike models). Data Engineers focus on data modeling, ETL, capacity calculations, reservations/utilization queries, and production SQL/Python tasks. For interview preparation, prioritize timed coding practice, system-design templates, rigorous SQL drills (joins/CTEs/aggregation), clear A/B-testing frameworks, and concise STAR behavioral stories tied to measurable impact.
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"I've used LC, Glassdoor, and random Discords. Nothing comes close to the accuracy here. The questions are actually current — that's what got me. Felt like I had a cheat sheet during the interview."
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"Coaches and bootcamp prep courses cost around $200-300 but PracHub Premium is actually less than a Netflix subscription. And it landed me a $178K offer."
"I honestly don't know how you guys gather so many real interview questions. It's almost scary. I walked into my Amazon loop and recognized 3 out of 4 problems from your database."
"Discovered PracHub 10 days before my interview. By day 5, I stopped being nervous. By interview day, I was actually excited to show what I knew."
"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."
"The search is what sold me. I typed in a really niche DP problem I got asked last year and it actually came up, full breakdown and everything. These guys are clearly updating it constantly."
Find shortest substring with N unique characters
You are given a string s and an integer n. Find the shortest contiguous substring of s that contains exactly n distinct characters. If there is no suc...
Design ticketing and coding practice platforms
You are asked two separate system design questions. --- 1. Design an online event ticketing platform (like Ticketmaster) Design a large-scale web serv...
How would you evaluate upranking Shop ads?
Meta is considering upranking ads that send users to an in-app Shop experience (for example, Facebook/Instagram Shops) relative to ads that send users...
Design and validate an ads feed experiment
This question evaluates a data scientist's competency in experiment design, causal inference, and applied statistical analysis for product experimenta...
Write SQL to compare social-only vs game-only engagement
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Estimate Portal’s causal lift on video-call usage
This question evaluates applied causal inference and statistical analysis skills, including defining estimands, designing staggered-adoption differenc...
Build a model to infer home vs office vs public
You must infer whether a Facebook session’s network context is home, office, or public venue to inform Portal targeting. Constraints: IPs may be share...
Design offline segments for Meta Portal retail
Meta Portal is a plug‑in home video‑calling device sold via offline retail. Target segments are not finalized. You have historical, anonymized Faceboo...
Size opportunity for new product line
An e-commerce site considers adding a "Home Office" product line. Before any A/B test, size the opportunity and recommend whether to proceed. Assumpti...
Evaluate and prioritize Facebook Groups
This question evaluates product analytics, experimentation design, causal inference, KPI hierarchy and metric-definition skills, and quantitative prio...
Design experiment for fake accounts impact
Experiment Design: Removing Detected Fake Accounts and Measuring Causal Impact Context: You are designing an end-to-end experiment on a large, interac...
Define and query shop visibility
You are given the following schema. Use only the columns provided; do not introduce new fields or labels. Tables and columns: - shops(shop_id INT, sho...
Design hashtag recommender with cold start
This question evaluates expertise in recommender-system design, feature engineering, ranking and learning-to-rank models, cold-start strategies, evalu...
Compare Instagram vs. Facebook using causal experiments
Compare Instagram and Facebook for consumer time and engagement: a) Define a single-objective OEC that captures healthy cross-app ecosystem value with...
Write dating profile report with final reviews
Today is 2025-09-01. You need a daily dating-profile quality and engagement report that only includes profiles whose latest version has a final approv...
Detect and address Simpson’s paradox
Experiment Aggregation Bias and Heterogeneity: Simpson's Paradox, Robust Estimation, and Decisioning Context You ran a randomized experiment measuring...
Control error under multiple testing
This question evaluates a candidate's understanding of multiple hypothesis testing, sequential monitoring, and error-rate control—specifically familyw...
Estimate variance for ratio metrics
KPI Variance via Delta Method and Inference Choices for ARPU Context You run experiments where each arm produces aggregate totals per analysis unit (e...
Diagnose a non-significant experiment outcome
A/B Test Interpretation, Power, and Decision-Making Under Asymmetric Loss Context You ran a two-sample A/B test on a primary mean metric (two-sided t-...
Design experiments under network interference
A/B Test Design for Search-Ranking in a Two-Sided Marketplace with Interference Context You need to evaluate a change to the search-ranking algorithm ...