Meta Data Scientist Machine Learning Interview Questions
Practice 50 real Machine Learning interview questions for Data Scientist roles at Meta.
"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."
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...
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
This question evaluates expertise in reinforcement learning and sequential decision-making for product optimization, covering MDP formulation, contras...
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 ...
Design a restaurant recommender under constraints
This question evaluates a candidate's competency in designing scalable machine learning recommender systems, covering retrieval and ranking architectu...
Build a Bayes classifier for reviewer types
This question evaluates Bayesian inference skills, including posterior updating under conditional independence, likelihood modeling for categorical ob...
What features and feature selection would you use?
Context You are building an ML system to rank/promote shop ads in an e-commerce feed/search page. At serving time, the system may score candidate shop...
Evaluate Classifier with Precision, Recall, and Fairness Metrics
Evaluate Classifier with Precision, Recall, and Fairness Metrics Offline Evaluation Framework for a Harmful-Content Video Classifier Context You are e...
Identify Features for Fake News Detection on Facebook
Identify Features for Fake News Detection on Facebook Design a Machine-Learning System to Flag Fake News on Facebook Scenario An increase in fake news...
Evaluate Factors Before Replacing Recommendation Model
Evaluate Factors Before Replacing a Recommendation Model A large ads platform has built a new recommendation or ranking model and plans to deprecate t...
Classify Reviewers Using Bayesian Probability for Accuracy Analysis
Classify Reviewers With Bayesian Probability You are auditing reviewers who may be lazy or careful. Each reviewer completes n gold-standard review tas...
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 ...
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...
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...
Choose ML metrics under asymmetric costs
This question evaluates a data scientist's competency in cost-sensitive binary classification, covering skills such as defining business cost matrices...
Model preference without ground truth
This question evaluates a data scientist's competency in uplift modeling, causal inference, experimental design, weak supervision, and bias and shift ...
Build predictive model for feature rollout targeting
Before global launch, you want to predict which users or products would benefit most from the 'More like this' button so you can stage rollout. Design...
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 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...
Design Machine Learning Model for Facebook Groups Post Ranking
Design Machine Learning Model for Facebook Groups Post Ranking ML System Design: Ranking Facebook Groups Posts in News Feed Scenario You are designing...