Meta Data Scientist Machine Learning Interview Questions
Practice 52 real Machine Learning interview questions for Data Scientist roles at Meta.
"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."
How would you design a Shop Ads ranking algorithm?
Context An ads ranking system serves ads via an auction. You want to uprank Shop Ads relative to Website Ads to improve user conversion and help certa...
Choose metrics for fake-user classifier
Classifying Fake Accounts: Metrics, Capacity, Thresholding, and Validation Context - Population: 10,000,000 daily active users (DAU) - True fake rate ...
Design an ad recommendation ranking approach
You are designing an ad recommendation (ad ranking) system for a consumer app. Goal Maximize long-term business value while maintaining a good user ex...
How would you predict a car’s turning intention?
At an intersection, there are n vehicles stopped or approaching. For each vehicle, you have a short history (e.g., last 3–10 seconds at 10 Hz) of: - P...
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...
Apply reinforcement learning to product decisions
Session‑level recommendations have stateful effects and feedback loops affecting long‑term retention. a) Formulate the problem as an MDP (state, actio...
Design a restaurant recommender under cold start
Design a Multi-Objective Restaurant Ranking System You own the restaurant recommendation surface for a city app. The goal is to rank nearby restaurant...
Identify Algorithms for Detecting Malicious Duplicated Content
Detecting Malicious Duplicated Text (DOT) Scenario You are selecting technical approaches for DOT, a bot‑detection tool aimed at finding malicious dup...
Design a System to Recommend Local Restaurant Profiles
Recommending Local Restaurant Pages in the News Feed Context Design a non-ads recommendation system within a large social media app to surface local r...
How would you design Shop-ad ranking?
Suppose the previous experiment shows that, in some contexts, users are more likely to convert when shown an ad that leads to an in-app Shop rather th...
Which clustering algorithm would you use and why
You need to cluster users for a social product. Part A (traditional clustering): - You are given a user feature table (dense numeric/categorical featu...
Propose an ads recommendation model for shop ads
You need to propose a modeling approach for recommending/ranking shop ads (i.e., which shop ads to show and in what order) for a marketplace app. Desc...
Design hashtag recommender with cold start
Hashtag Recommendation Design (Short-Video App) Task Design a system to recommend hashtags a user is likely to follow. Answer all parts precisely. 1) ...
Choose and compute recommender evaluation metrics
Restaurant Recommender: Offline Evaluation and Modeling Context: You are scoring p(y=1|x) with logistic regression to predict if a user will engage wi...
Detect leakage and evaluate a prediction model
Churn Prediction Model: Leakage, Validation, KPIs, Interpretation, Monitoring Context: You inherit a weekly-scored model that predicts whether a user ...
Identify Fake Accounts Using Machine Learning Techniques
Scenario You are a data scientist at a social‑commerce platform responsible for trust and safety. You need to design a system to detect and mitigate f...
Design bot detection and evaluate trade-offs
Bot-Detection System Design for Comment Activity Context You are designing and evaluating a machine learning system to detect automated (bot) comment ...
Deploy multi-armed bandits safely
Online bandit with 3 variants, churn guardrail, and delayed conversions Context You are running an online experiment with 3 variants (including contro...
How to design Shop ad ranking
Suppose the experiment suggests that increasing exposure for Shop ads may be beneficial. The interviewer then asks how you would design the ranking al...
Design an ad recommendation and ranking system
You are building an ad recommendation/ranking system for a content feed (e.g., short-form videos). At each feed position, you may show either an organ...