Meta Analytics & Experimentation Interview Questions
Practice 1,159 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.
"I got asked a hardcore MCM DP question and I saw it on PracHub as well. Solved that question in 5 minutes. Without PracHub I doubt I could solve it in 5 hours. Though somehow didn't get hired, perhaps I guess I solved it too fast? /s"
"Believe me i'm a student here jn US. Recently interviewed for MSFT. They asked me exact question from PracHub. I saw it the night before and ignored it cause why waste time on random sites. I legit wanna go back and redo this whole thing if I had chance. Not saying will work for everyone but there is certainly some merit to that website. And i'm gonna use it in future prep from now on like lc tagged"
"10 years of experience but never worked at a top company. PracHub's senior-level questions helped me break into FAANG at 35. Age is just a number."
"I was skeptical about the 'real questions' claim, so I put it to the test. I searched for the exact question I got grilled on at my last Meta onsite... and it was right there. Word for word."
"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."
"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."
"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."
"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."
"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."
"Literally just signed a $600k offer. I only had 2 weeks to prep, so I focused entirely on the company-tagged lists here. If you're targeting L5+, don't overthink it."
"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."
Evaluate Impact of Increasing Stranger Content in Feeds
Evaluate Impact of Increasing Stranger Content in Feeds Feed-Ranking Strategy: Friends vs. Stranger Content Background A personalized feed currently m...
Determine High-Quality Notifications with CTR Analysis
Determine High-Quality Notifications with CTR Analysis Push Notification Quality: Metric, Baseline Assessment, and Experiment Design Background A mobi...
Design A/B Test to Evaluate New Video-Feed Feature
Design A/B Test to Evaluate New Video-Feed Feature Scenario A consumer social-media app is launching a short‑video feed (TikTok-style). A newly added ...
Identify Metrics to Detect Fake-Account Activity on Facebook
Identify Metrics to Detect Fake-Account Activity on Facebook Detecting and Measuring Fake Accounts Scenario Facebook wants to understand and curb fake...
Evaluate Facebook Groups Metrics and Test Comment-Collapsing Feature
Evaluate Facebook Groups Metrics and Test Comment-Collapsing Feature Facebook Groups Product Health and Feature Experiment Design Context You are eval...
Design an A/B Test for Group Video Calls Impact
Design an A/B Test for Group Video Calls Impact A/B Experiment Design: Group Video Calls on Instagram Scenario Instagram wants to evaluate the impact ...
Analyze Algorithm's Impact on Diverse Demographics and Validate Causes
Analyze Algorithm's Impact on Diverse Demographics and Validate Causes A/B Test: Heterogeneous Lift in CTR for a New Ad-Ranking Algorithm Context You ...
Analyze Seller Activity and Vehicle Listing Interactions
Analyze Seller Activity and Vehicle Listing Interactions listing_interaction +-----------+-----------+------------+------------+----+ | buyer_id | se...
Design Sampling Strategy to Estimate Fake News Proportion
Design Sampling Strategy to Estimate Fake News Proportion Estimating Fake News Prevalence and Impact on Facebook Context Management is concerned about...
Evaluate Instagram Shopping Tab Success with Key Metrics
Evaluate Instagram Shopping Tab Success with Key Metrics Instagram Shopping Tab: Post-Launch Evaluation and Sizing Context You are evaluating the succ...
Assess Cultural Fit and Problem-Solving in Reality Labs Role
Assess Cultural Fit and Problem-Solving in Reality Labs Role Behavioral and Leadership Interview Prompts (Data Scientist, Reality Labs) Context The hi...
Determine Success Metrics for Instagram Video-Call Feature
Determine Success Metrics for Instagram Video-Call Feature Instagram Group Video-Call MVP: Defining Success and Metrics Context You are the data scien...
Calculate and Compare Survey Response Rates for User Tenure
Surveys +--------+------------+--------------+----------+ | userid | date | survey_event | response | +--------+------------+--------------+----...
Determine Value of Prioritizing Accounts by Unread Notifications
Determine Value of Prioritizing Accounts by Unread Notifications Feature Validation: Ordering Multiple Accounts by Unread Notifications Context Users ...
Diagnose Causes of Low Retention for FB Light
Diagnose Causes of Low Retention for FB Light Diagnose Low Retention for FB Light (Android-only, Emerging Markets) Context You are a data scientist on...
Analyze Change in App Metrics and Feature Impact
Analyze Change in App Metrics and Feature Impact Scenario A consumer app has either launched a new feature or observed a sudden change in a key metric...
Determine Significance of Model B's Performance Improvement
Determine Significance of Model B's Performance Improvement A/B Test: Two-Proportion Z-Test for Success Rates Scenario You ran an A/B test comparing t...
Detect and Reduce Spammy Friend Requests Effectively
Detect and Reduce Spammy Friend Requests Effectively Detecting Spammy Friend Requests Context Assume a consumer social platform where users can send f...
Explain Type I vs. Type II Errors in A/B Testing
Explain Type I vs. Type II Errors in A/B Testing A/B Testing Errors and Estimation Under Skewed Metrics Context You are analyzing an A/B experiment fo...
Evaluate Probability of Positive User Comments and Model Performance
Evaluate Probability of Positive User Comments and Model Performance Social-Media Positivity: Independence and Model Comparison Context You are evalua...