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."
What are linear regression assumptions?
You fit an ordinary least squares (OLS) linear regression model. 1) What are the key assumptions behind OLS (for unbiasedness and for valid inference)...
Analyze Product Launch and Creator Engagement
You are interviewing for a Data Scientist intern role at a short-video platform. Use a recent data or machine-learning project from your resume as the...
Adjust YouTube Ad Scores Using Mixed-Effects Linear Regression
Scenario - 100 reviewers each rate the same 100 YouTube ads on a 1–10 scale. - Ratings may be systematically higher or lower for some reviewers (lenie...
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:...
Evaluate Python Class Design in Data Pipeline
Scenario You are reviewing a Python class used in an ML/data pipeline that follows the scikit-learn-style fit/transform pattern. Assume a typical tran...
Detect Data Leakage in Supervised Learning Pipelines
ML Take‑home: Bias–Variance, Regularization, Leakage, and From‑scratch Logistic Regression Context You are given user event logs in a Pandas dataframe...
When prioritize precision vs recall
Context You are working on a product team and building (or evaluating) a binary classifier that triggers an action (e.g., show a warning, block conten...
Explain normal distribution and standardize it
Statistics / Quant Risk Interview Question You are interviewing for a quant risk–leaning role. 1. What are the key characteristics (properties) of a n...
Design features for house price prediction
Scenario You are building a model to predict house sale price from a tabular dataset (similar to typical real-estate datasets). The interviewer expect...
Analyze trading RFQ competitiveness data
RFQ Competitiveness Analysis in Excel You are given an Excel file containing a few months of trading RFQ (request-for-quote) data for a sales & tradin...
Find companies similar to a given client
System Design: Retrieve Top-20 Most Similar Companies for Sales Prospecting You are given an anchor client (e.g., The Coca‑Cola Company). Design a sys...
Extract companies from noisy text
Extracting Company Names from Noisy Resumes and Web Snippets Context You receive messy resume text (PDF-to-text/OCR, varying casing) and scraped web s...
Contrast L1 and L2 regularization effects
Ridge (L2) vs Lasso (L1) in Linear and Logistic Regression Context: You are comparing L2 (Ridge) and L1 (Lasso) regularization for linear and logistic...
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...
Design and evaluate an uplift model
Targeting a 20% Subset With a Free-Delivery Promotion to Maximize Incremental Orders per Dollar Context You work on a two-sided delivery marketplace a...
Design classification under missingness and imbalance
30-Day Readmission Classifier: End-to-End Plan Context: You are building a binary classifier to predict 30-day readmission using claims and EHR featur...
Design a model for subscription adoption prediction
Predicting 60-Day Adoption of Subscription by Non-Subscription Merchants Context You need to predict which merchants who are not currently using the S...
Design email to avoid Promotions without online tests
Offline Design of a Transactional Email to Minimize Promotions/Spam Classification Context You must finalize the design of a single in‑game transactio...
Diagnose overfitting, DenseNet, preprocessing, CV
ML Interview Task: Overfitting, DenseNet vs. ResNet, Medical Imaging Pipeline, Hyperparameter Tuning, and Cross-Validation 1) Overfitting - Define ove...
Implement random forest with OOB and imbalance
Implement a Memory-Efficient Random Forest (Binary Classification) Under Constraints You are asked to design and implement a Random Forest for binary ...