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 ML metrics under asymmetric costs
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Explain MSE vs MAE, AUC, and imbalance handling
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Choose metrics for fake-user classifier
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Design a Cold-Start-Aware Recommender
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Derive and compare core ML and RL methods
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Rank features using logistic regression coefficients
You are given a binary classification dataset: - X: a 2D array of shape (n_samples, n_features) containing numeric features - y: a 1D binary array of ...
Verify Machine-Learning Fundamentals for E-commerce Recommendation Platform
Rapid ML Fundamentals Check — Recommender Systems Context You are interviewing for a data-science role on an e‑commerce recommendation platform. The h...
Address Missing Income Bracket in California Housing Data
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Explain Linear Regression to Non-Technical Stakeholders
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Build Classifier: Evaluate with AUROC for Imbalanced Data
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Choose Metrics for Evaluating Fake-User Classifier
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Optimize Feature Selection and Handling in Machine Learning Models
Scenario You are building a customer propensity model to predict the probability that a user will take a desired action (e.g., purchase, subscribe). Y...
Build Accurate Energy Consumption Prediction Model for Utilities
Predicting Daily Energy Consumption: End-to-End Regression to Production Context You need to build and productionize a supervised regression model tha...
Explain Overfitting and Transformer Basics
Answer the following machine learning questions in a self-contained way: 1. What is overfitting? How would you recognize it from training and validati...
Explain why LASSO selects features
Explain why LASSO performs feature selection. Provide: 1) high-level intuition comparing L1 vs. L2 penalties; 2) geometric interpretation of the const...
Design a Regression Model for Robust Extrapolation Performance
Scenario Onsite machine-learning exercise: your task is to build a regression model using only numerical features that not only fits training data but...
Determine Features for Effective Hashtag Recommendations
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Employ Collaborative Filtering for Personalized Recommendation Lists
Scenario You are releasing a new recommendation feature that must generate and assign personalized, ranked product lists for each user at scale. Users...
Address Overfitting in Supervised Learning Models
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