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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Compare performance of FB vs IG Stories
This question evaluates a data scientist's competency in experimental design, causal inference, attribution modeling, metric selection, and decision-o...
Compute this-year spend share of last-year whales
This question evaluates proficiency in data manipulation and analytics engineering, specifically SQL and Python skills for aggregations, joins, calend...
Design weapon-selling ad detection from posts
This question evaluates a candidate's ability to design a production-scale multimodal ML system for detecting weapon-selling ads, testing competencies...
Calculate Expected Day for First Selection in Sampling
Expected Day of First Selection in Daily Sampling There are 1,000 people. Each day, 10 distinct names are selected uniformly at random. Day counting s...
How would you design a Shop Ads ranking algorithm?
This question evaluates a candidate's understanding of machine learning-driven ad ranking, auction mechanics, multi-stakeholder objective formulation,...
Design content moderation for a posting app
This question evaluates a candidate's ability to design content-moderation features, covering competencies in scalable system design, API and data mod...
Implement weighted random sampling with preprocessing
This question evaluates algorithm design and probabilistic reasoning for weighted random sampling, including data-structure preprocessing, time-space ...
Solve Two Backtracking Array Problems
You will solve two independent coding problems. For each problem, first discuss edge cases, then implement a correct solution, and finally explain how...
Design Real-Time Auctions for Social Posts
Design a real-time auction feature for a large social photo and video app. A creator can attach an auction to a post. Viewers can place bids, and ever...
Design a system to detect weapon posts
This question evaluates system design and machine learning engineering competencies, including multi-modal content detection, real-time model serving,...
Design a Top-K trending items service
This question evaluates competency in large-scale system design, real-time streaming ingestion, distributed aggregation, and trade-offs between exact ...
Compute ad revenue metrics by geography in SQL
You work on a marketplace app that shows shop ads. You are given the following tables. Assumptions - All timestamps are stored in UTC. - “Revenue” is ...
Choose threshold under asymmetric costs
You own a credit-card fraud classifier deployed as a probability scorer. Choose an operating threshold under asymmetric costs and justify it quantitat...
Replace legacy ads model safely
Facebook Ads Ranking Replacement: M0 to M1 You are asked to replace a legacy ads ranking model (M0) with a new model (M1) in a large-scale feed ads sy...
Compute p-values, power, and adjust errors
Statistics Interview Task (Onsite) You are evaluating a product experiment and related analytics questions. Answer precisely, showing calculations and...
Design an A/B test for pinned-unread feature
Experiment Design: Evaluating a Pinned-Unread Chat Feature Context You are evaluating a new messaging feature that pins chats with unread messages to ...
Design a hashtag recommender for News Feed
Design: Hashtag Recommendations in the News Feed Context You are adding hashtag recommendations alongside posts in a large social app’s News Feed. The...
Compute sample size and test duration correctly
Powering Two Online Experiments: Sample Size, Duration, and Design Defenses You are designing experiments to improve a friend-accept rate metric in a ...
Analyze daily comments distribution and sampling
Daily Comments per Active User: Sampling and Inference You have, for a given day d, the count of comments made by each active user. Let there be m act...
Navigate reschedules, offers, and team-match uncertainty
Behavioral + Due Diligence + Risk Management (Data Scientist — Onsite) Context You are a Data Scientist candidate approaching an onsite. You are juggl...