Data Scientist Machine Learning Interview Questions
Practice 434 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."
Explain RF optimization and variable-importance pitfalls
Optimize and Regularize a Random Forest Regressor for Tabular Data Context: You are training a Random Forest (RF) regressor on tabular data and need t...
Predict and act on contract renewal risk
Predicting Enterprise Contract Renewal After a Quality Incident Context A video-conferencing provider experienced a spike in call disconnects. You nee...
Explain AUC, imbalance, losses, and networks
This question evaluates a candidate's understanding of imbalanced classification and regression concepts, including ROC/PR curves and AUC, prevalence ...
Decide when to model courier ETA
This question evaluates a candidate's competency in machine learning product decisions—covering target definition, dispatch-time feature design, offli...
Achieve 0.95 precision via thresholding
Deploying a High-Precision Classifier on an Imbalanced Dataset You are given a binary classification problem with 50,000 samples and ~5% positives. Th...
Design a short-video recommendation system
Design a recommendation system for a short-video feed product. Your answer should cover the full pipeline: 1. Objective and labels: Define what the sy...
How do you choose a classification threshold?
Context You built a binary sentiment classification model (e.g., positive vs. negative) and need to deploy it in a product where actions depend on the...
Implement Streaming Clustering for Numbers
You receive a continuous stream of numeric values. Choose an appropriate clustering algorithm and implement it so that each incoming number can be ass...
Fit Linear Regression: Analyze Economic Impact of Coefficients
Fit Linear Regression: Analyze Economic Impact of Coefficients Scenario You are given a tabular financial dataset df where the column target is the de...
Differentiate Overfitting and Underfitting in Machine Learning
Differentiate Overfitting and Underfitting in Machine Learning ML/DL Fundamentals for a Recommendation Engine Context You are preparing for a take-hom...
Design an Automated Home-Price Valuation Model
Design an Automated Home-Price Valuation Model Scenario You are building an automated house-price valuation service for a real-estate platform. Questi...
Explain L1 vs L2 and ridge vs lasso
Explain the differences between: 1. L1 vs L2 regularization (how they change the objective, geometry/intuitions, and typical effects on learned parame...
Run EDA and train models while preventing overfitting
This question evaluates proficiency in exploratory data analysis, feature preprocessing, baseline linear regression and small neural network training,...
Build a fair loan classifier
You are given a dataset of loan applicants. Each row represents one loan application and contains applicant attributes, loan attributes, and a binary ...
Forecast bikes available at a station
This question evaluates proficiency in time-series forecasting, feature engineering, handling temporal data splits, and incorporating operational cons...
Trading Game: Expected-Value Betting, Kelly Sizing, and Arbitrage Under Time Pressure
You are in a live 45-minute trading-game round at a proprietary-trading / market-making firm. You start with a bankroll of 1,000 (game money). The gam...
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...
Handle imbalance, sampling, and overfitting
Machine Learning Fundamentals: Imbalance, Sampling, Overfitting, and Regularization You are asked several machine learning fundamentals questions in a...
Explain SHAP and build an ML project
This question evaluates understanding of model explainability using SHAP and the competency to design and operationalize an end-to-end machine learnin...
Build and evaluate bad-link classifier
You have 1,000 URLs labeled as bad or good and a much larger unlabeled pool, with bad links rare. Design features and train a logistic regression. Exp...