Data Scientist Interview Questions
Practice 2,964 real Data Scientist interview questions for 2026. Data Scientist interview questions drawn from Meta, Capital One, Amazon, Google, TikTok and similar employers — real questions from actual interviews with detailed solutions — designed to accelerate your interview preparation for product analytics, ML and production data roles. This collection emphasizes the practical skills interviewers test: SQL and data manipulation, experiment design and A/B testing, statistical reasoning, Python coding for data problems, model evaluation and feature engineering, plus machine-learning system tradeoffs and metric design. What’s distinctive about modern data-science loops is the blend of product thinking and reproducible ML: expect hands-on SQL tasks and funnel analysis in screens, deeper experiment-design and causality questions in mid rounds, and coding or modeling challenges plus ML-system discussions in senior loops. Interviewers evaluate problem framing, statistical rigor, and how you communicate decisions to product partners. To prepare, prioritize daily SQL practice (CTEs, window functions), refresh hypothesis-testing and power calculations, rehearse concise metric-driven narratives, and build a few end-to-end model or experiment stories you can explain clearly under time pressure.
"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 and compute correct t-test
A/B Test: Watch Time per Impression (seconds) You ran an experiment with two independent groups and want to assess whether the new experience increase...
Interpret p=0.10 rigorously
A/B Test on Monthly Churn: Inference, Power, and Testing Choices You ran a 28-day A/B test to reduce monthly churn among subscribers, randomizing 150,...
Design metrics and experiment
Context You are the data scientist designing success metrics and an experiment for a new subscriber-only feature in a consumer subscription product (e...
Align with PM on ranking goals
Stakeholder Alignment and De-risking a Home Page Product Ranking Initiative Context You are a data scientist asked by a PM to "rank products on the ho...
Design and justify unread-accounts pinning experiment
Experiment Design: Pin Unread Accounts at Top of Account Switcher Context You propose a feature for users who own multiple accounts (same person_id): ...
Resolve conflict and learn from failure
Behavioral Prompt for Data Scientist (HR Screen) Provide two concise, structured responses. Use STAR (Situation, Task, Action, Result) and quantify ou...
Interpret A/B results with p-values and uncertainty
A/B Test: Effect Sizes, CIs, Multiple Testing, Power, and Decision Context: You ran a 14‑day experiment (2025‑08‑15 → 2025‑08‑28) with 1:1 allocation ...
Formulate hypotheses and metrics for video-pin ramp
Experiment Design: Increasing Video Pins in Pinterest Home Feed Context Pinterest wants to increase the proportion of video pins in the Home Feed to b...
Price a coin-doubling game rationally
Coin-Doubling (St. Petersburg) Game: EV, Log-Utility Pricing, Kelly Staking, and House Cap Context and assumptions - Single play: You buy one ticket t...
Compare average profit across mix scenarios
Burger Profit Mix — Scenario A vs. Scenario B Context: You sell two burger types (Regular and Vegan). In Scenario A, you sell only Regular. In Scenari...
Compare CNN, RNN, and LSTM rigorously
Sequence Modeling: Rigorous Comparison of CNNs, RNNs, and LSTMs Context and assumptions: - We are modeling 1D sequences of shape (batch=32, time=100, ...
Design a fintech homepage ranker
Personalized Product Ranking for a Fintech Home Page — End-to-End Design Context You are designing a personalized ranking system for a fintech app’s h...
Compute fraud probabilities with Bayes and Binomial
Fake-Account Detection with Binomial Sessions and Bayes Updating You are evaluating a rules-based detector for fake accounts on an online platform. Ea...
Estimate fake-account prevalence with capture-recapture
Capture–Recapture Estimation with Two Detectors You are evaluating suspected fake accounts on a platform with 50 million active accounts. In one week:...
Design a restaurant recommender under cold start
Design a Multi-Objective Restaurant Ranking System You own the restaurant recommendation surface for a city app. The goal is to rank nearby restaurant...
Design and explain robust web APIs for ML inference
Design an HTTP API for Image-Based Model Predictions Context: Design an HTTP REST API that serves predictions for image inputs (e.g., classification, ...
Assess SQL cleaning, mapping, joins, keys, and DDL/DML
You inherit a small retail analytics warehouse. Use the schema and sample rows below to answer all parts. Schema and sample data (minimal rows shown):...
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...
Test whether samples follow a binomial distribution
You collect a dataset that you believe comes from a binomial process. Each observation is a count of successes. - You have i.i.d. samples \(x_1,\dots,...
Solve core probability/statistics mini-problems
Answer the following probability/statistics interview questions. Assume all randomness is independent unless stated otherwise. 1) Radioactive decay (h...