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."
Improve low R² without p‑hacking
Predicting Contribution per Order with Low R² Context You are modeling contribution per order (a continuous per-order outcome such as margin or profit...
Design a battery-life predictor and cold-start strategy
Smartphone Time-to-Empty (TTE) Prediction — Baseline, Features, Cold Start, Evaluation, and Monitoring Context You are building a per-device predictor...
Design real-time payments fraud model under constraints
Real-Time ML Policy Design: Prevent Unauthorized Purchases by Minors Context: You need to reduce unauthorized purchases by minors using their parents'...
Explain SHAP vs VIF under collinearity
High Collinearity in Binary Classification: VIF, SHAP, and Interpretation Strategy You are modeling a binary outcome Y. Two numeric features A and B a...
Explain variance reduction in random forests
Consider a random forest (or bagged ensemble) that predicts at a fixed input \(x\) by averaging \(B\) tree predictions: \[ \hat f_B(x) = \frac{1}{B}\s...
Design a house-price prediction model
Problem You are asked to build a model to predict house sale prices for a city of your choice. Data (assume typical real-estate fields) You have a his...
Fit logistic regression and return top features
You are given: - X: a 2D numeric array where each row is a feature and each column is an observation (shape: n_features x n_samples). - feature_names:...
Which clustering algorithm would you use and why
Question You need to cluster users for a social product (e.g. Meta) to discover meaningful groups such as communities, interest groups, or usage segme...
Explain Train-Test Performance Gap
A supervised model for a TikTok-like product problem performs very well on the training set but much worse on a held-out test set. How would you diagn...
Design a robust fraud detection system
Real-Time Card Fraud Detector — End-to-End Design Context - Fraud base rate ≈ 0.2% (severe class imbalance) - Labels arrive with a 14-day delay (e.g.,...
Design a leak-free time-split model
Predict 30-Day Purchase Probability at a Snapshot (Technical Screen) Assume you have user, event, and order data with two timestamps per row: - event_...
Model flight delays with EDA and explanation
Predicting 15+ Minute Arrival Delays at Scheduled-Departure Time You are building a binary classifier that predicts whether a domestic flight will arr...
Build a Bayes classifier for reviewer types
Bayesian Reviewer-Type Inference Setup There are two reviewer types: - Lazy (prior probability 0.20): always gives a "Good" review. - Careful (prior p...
Implement robust k-means from scratch
Implement K-Means Clustering From Scratch (Production-Ready) Context You are asked to implement K-Means clustering from scratch for a machine learning...
Identify Risks and Improve Imputation Class Implementations
Scenario You are reviewing three custom Python imputation classes intended for use in a scikit-learn workflow. Each class fills missing values column-...
Fit Linear Regression: Analyze Economic Impact of Coefficients
Scenario You are given a tabular financial dataset df where the column target is the dependent variable (e.g., next-period return or excess return), a...
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...
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...
Explain deployment, retrieval, and regularization
You are interviewing for a machine-learning role at a large-scale short-video platform. Answer the following conceptual questions. 1. Under tight GPU ...
Diagnose overfitting from error curves
You are evaluating a supervised machine learning model. You are shown a plot where the x-axis is training epoch or model complexity and the y-axis is ...