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."
Compute unread and multi-account user percentages
You’re given two tables. Write ANSI-SQL to answer parts (a)–(d). Treat a notification as unread if read_at IS NULL. Denominator for user-level percent...
Choose a precise A/B test primary metric
A/B Test: Choose One Primary Metric for a Home-Screen CTA Color Change You are running an A/B test for an app that changes the color of its primary ho...
Measure and mitigate notification spam
Facebook sends many notification types (e.g., friends' posts, comments, birthdays, events). Design a rigorous measurement plan to determine whether ou...
Design cross-validation; explain bias–variance
Define cross-validation rigorously and compare k-fold, stratified k-fold, leave-one-out, nested CV, and time-series rolling/blocked CV. For a dataset ...
Demonstrate ownership and navigate challenges
Behavioral deep dive: 1) Describe the most impactful modeling project you led end‑to‑end—your role, the concrete business metric moved, and one hard t...
Transform messy transactions with pandas
You are given two CSVs. transactions.csv - Columns: txn_id, user_id, ts_iso (ISO8601 with timezone), amount (decimal USD; refunds negative), merchant_...
Write SQL for noisy A/B launch metrics
PostgreSQL. Today is 2025-09-01. You’re given the following schema and toy samples: users(user_id INT, country TEXT, signup_date DATE, marketing_chann...
Diagnose location-sorted recommender causing revenue drop
Eats recommendations were changed to rank items primarily by distance to the user; after launch, add-to-cart rate rose but revenue per session fell. D...
Design station experiment with interference and rush-hour spillovers
Experiment Design Under Interference for an In‑Station Ordering Pilot Context (Completed) You are evaluating two competing in‑station ordering feature...
Write SQL for hashtag analytics and joins
Assume today = 2025-09-01. Schema and small sample data are below. Use ANSI SQL; explain any dialect-specific functions you choose. Where asked, expla...
Size opportunity and prioritize experiments
New E‑commerce Product Line: Pre‑Investment Quantification and Test Plan You are evaluating whether to invest engineering and operational resources to...
Choose ML metrics under asymmetric costs
Binary Classifier With Asymmetric Costs: Fraud vs. Cancer Context: You own a production binary classifier and must make product/ML decisions under asy...
Select and prioritize metrics with guardrails
Design a Metrics Framework for a New Groups Stories Feature Context You are evaluating a new Groups Stories feature whose goal is to increase meaningf...
Define and compute surge pricing metrics
Surge Pricing Metrics, Formulas, and Causal Estimation You are evaluating surge pricing in a two-sided marketplace (customers place requests; drivers/...
Implement and extend My Calendar III
Design and implement a booking system like LeetCode 732 (My Calendar III). Provide a class with methods: book(start, end) using half-open intervals [s...
Demonstrate leadership in cross-functional disagreement
Behavioral & Leadership (HR Screen, Data Scientist) Prompt Describe a time you disagreed with a partner team (e.g., product pushing for more aggressiv...
Explain complex tech to non-technical stakeholder
Behavioral: Explain a Complex Modeling Decision to a Non‑Technical Sales Leader You are asked to explain a complex modeling decision from a résumé pro...
Implement weighted sampling without replacement
Implement in Python a function sample_k(items, weights, k) that returns k items without replacement with probability proportional to weight. Requireme...
Measure driver experience quantitatively
Driver Experience Index (DEI) — Design, Validation, Debiasing, and Experimentation Context: You are a Data Scientist at a ride-hailing company. Define...
Write SQL for engagement and attribution KPIs
Using the schema and sample data below, answer the SQL tasks. Assume timestamps are UTC and comments with is_deleted=1 do not count. Schema: users(use...