Data Scientist Machine Learning Interview Questions
Practice 399 real Machine Learning interview questions for Data Scientist roles. From companies including Meta, Amazon, Google, Capital One, TikTok.
"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."
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...
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...
Choose clustering vs regression; explain KNN
When would you use clustering vs. regression on a business problem with partially labeled outcomes? Specify the decision criteria (label availability,...
Choose and justify ML algorithms for tabular prediction
You must choose an algorithm for tabular prediction of arrival delay under these constraints: 500k rows, 120 features (mixed numeric/categorical with ...
Build and evaluate imbalanced binary classifier
Take‑home: Imbalanced Binary Classification with Temporal Split, Calibration, and Operating Point Selection Context You are given an event‑level datas...
Tune classifier and compute key metrics
Payment Error Classifier — Evaluation, Thresholding, and Cost-Sensitive Design Context You built a binary classifier to flag incorrect payments (posit...
Build a package-allocation model for couriers
Automatic Package-to-Courier Assignment with ML + Optimization You previously assigned packages to couriers manually. Design an end-to-end system that...
Select the better $5 promo-targeting model
Coupon Targeting Under a Daily Budget: Policy, OPE, Calibration, and Monitoring Context - You have two user-scoring models for a $5 coupon: M0 (curren...
Explain and tune XGBoost; prevent overfitting
XGBoost Tree Booster: Objective, Hyperparameters, Tuning for Imbalanced Detection, and Post-training Use Context: You are building a binary classifier...
Validate and monitor ranking model end-to-end
Expedia Hotel-Ranking Model: Evaluation, Metrics, Diagnostics, Rollout, and KPI Alignment Context: You are building a learning-to-rank (LTR) model to ...
Detect clickbait without labels, then supervise
Detecting Clickbait Ads Without Labeled Data Context You are asked to detect clickbait ad creatives when there is no labeled training data. You have i...
Explain OS usage gap via trees
iOS vs. Android Usage Gap: Modeling, Causality, Telemetry, Missing Data, and Segmented Actions Context You observe that Instagram usage is substantial...
Apply Double ML with text-address features
Estimate the ATE of a First Reminder on CSAT via Double Machine Learning (DML) Context You have observational data on customer satisfaction (CSAT) sur...
Explain a favorite model end-to-end
Predictive Model Deep-Dive (End-to-End) Pick one predictive model you know deeply (e.g., logistic regression, gradient-boosted trees, transformer clas...
Compare CNN, RNN, and LSTM rigorously
Sequence Modeling: Rigorous Comparison of CNNs, RNNs, and LSTMs Context and assumptions: - We are modeling 1D sequences of shape (batch=32, time=100, ...
Design a fintech homepage ranker
Personalized Product Ranking for a Fintech Home Page — End-to-End Design Context You are designing a personalized ranking system for a fintech app’s h...
Contrast LSTM and Transformer for long sequences
Train a Long-Context Autoregressive LM (T = 8192, H = 512, B = 8) You are training an autoregressive language model with: - Sequence length T = 8192 t...
Compare bagging vs boosting on imbalanced data
Fraud Detection on 10M Time-Ordered Transactions (0.5% Fraud) You are building a binary classifier to detect 0.5% fraudulent events among 10,000,000 t...
Predict Customer Churn with Machine Learning Workflow
Predicting Monthly Churn: End-to-End Workflow Scenario A subscription platform wants to predict whether a customer will churn in the next month. Assum...
Diagnose Multicollinearity in Flight Delay Prediction Model
Flight Delay Prediction — Data Quality, Modeling Choice, and Multicollinearity Scenario You have historical flight operations and weather data and nee...