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."
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...
Optimize IG Shopping ranking with multiple objectives
Instagram Shopping: Multi-Objective Ranking With Fairness, Fraud Robustness, and On-Device Constraints You are designing the Instagram Shopping home f...
Analyze overfitting, DenseNet, preprocessing, and cross-validation
Image Classification in Healthcare: End-to-End Interview Task Context: You are designing and evaluating an image-classification system for a healthcar...
Define scalable train/validation for churn
Weekly Churn Prediction: Training/Validation/Evaluation Plan Context You are building a weekly churn prediction model for a streaming service with: - ...
Estimate heterogeneous treatment effects with causal ML
Context You are given large-scale, logged observational data from an always-on promotion. Each record contains features X (user/context), a binary tre...
Explain factor leakage checks and IC/ICIR filtering
You’re interviewing for a quantitative/alpha role and have built predictive factors (features) for returns. Answer the following (conceptual) question...
Optimize Hyper-parameter Search to Prevent Combinatorial Explosion
Enumerate Grid-Search Hyperparameter Combinations and Manage Explosion Context You are building a hyper-parameter optimization service that must enume...
Optimize Predictive Analytics: Feature Engineering to Model Evaluation
End-to-End Predictive Analytics Project Walkthrough Context You are interviewing for a Data Scientist role. The interviewer asks you to walk through a...
Design and Validate Initial Restaurant Recommendation Model
Restaurant Recommendations on Facebook — First-Iteration Model Scenario You are tasked with designing a first-iteration machine-learning system to rec...
Compare Random Forests and Boosted Trees: Bias, Variance, Speed
Scenario Product-facing data-science interview on choosing and configuring tree-based ensemble models. The team wants to understand the trade-offs bet...
Address Fraud Detection with Imbalance and Concept Drift Solutions
End-to-End ML Workflow: Online Payments Fraud Detection Scenario You are designing a fraud-detection system for an online payments product that must s...
Classify Reviewers Using Bayesian Probability for Accuracy Analysis
Scenario Classifying reviewers as lazy or careful with limited labels Context (completed) You are auditing a pool of reviewers who can be either: - La...
Optimize Email Strategy for New Prime Video Series Launch
Scenario Designing, deploying, and evaluating ranking models and marketing emails for Prime Video. Question How would you approach sending marketing e...
Derive correlation bounds and omitted-variable bias
Core Statistics Prompt This is the core statistics round of a multi-stage Data Scientist interview. It bundles two independent statistics questions. T...
What features and feature selection would you use?
Context You are building an ML system to rank/promote shop ads in an e-commerce feed/search page. At serving time, the system may score candidate shop...
Optimize Churn Prediction: Feature Engineering and Model Selection
Weekly Churn Prediction (10M users): Feature Engineering, Model Choice, Explainability, and Debugging Scenario You own a weekly churn-prediction pipel...
Personalize Ad Delivery Using Machine Learning Techniques
Personalized Delivery of Three Ad Categories Scenario You operate a consumer feed with a single ad opportunity per request and three possible ad categ...
Predict Next-Period Conversion Rate Using Historical Campaign Data
Predicting Next-Period Conversion Rate from Campaign Logs Context You have historical campaign panel data with columns: adid, date, impressions, click...
Describe Building and Deploying a Machine Learning Model
Technical Onsite Scenario: End-to-End ML Project Deep Dive Prompt Describe a machine learning model you built in a recent project. Address: 1. What bu...
Design Push-Notification System for Airport Surge Pricing
Designing Airport Surge Push Notifications for Drivers Context You are building a real-time system for a ride-hailing platform. When an airport experi...