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."
Evaluate Stripe Capital Lending Strategy
Stripe is considering expanding Stripe Capital, a lending product for existing merchants on the platform. Eligible merchants receive a pre-qualified w...
How would you decide to cancel a TV show?
Case: Should you cancel, keep, or sell a TV series? You are the CEO of a streaming company. Your platform currently produces and distributes a scripte...
Implement K-means and handle train-inference mismatch
Part A — K-means (implementation + concepts) You are given a dataset \(X \in \mathbb{R}^{n \times d}\) and an integer \(k\). 1. Explain K-means: what ...
Design and Test a New Feature
You are interviewing for a Data Scientist internship at Uber. Assume the Uber rider app already includes standard functionality such as booking a ride...
Compute article-type diversity per user and histogram
You track article views and article metadata. Tables article_views - user_id INT - article_id INT - view_date DATE articles - article_id INT (PK) - ar...
Decide Which Show to Renew
You are a data scientist at a streaming company deciding whether to renew or cancel content over a 2-year planning horizon. Assume the following: - Ea...
Decide on vegan-burger R&D investment
Investment Decision: Vegan Burger R&D and Launch Business Case You are evaluating whether to invest now in R&D to develop and launch a plant-based (ve...
Write SQL for cuisine median delivery times
Use SQL to answer the following. Assume ANSI SQL with window functions and percentile functions available. Treat “today” as 2025-09-01 (inclusive). Co...
Compute ITT, TOT, and LATE with noncompliance
In the same personalization experiment, not everyone assigned to treatment actually receives personalization (noncompliance). You are given user-level...
Explain Linear Regression Assumptions
Suppose you are using ordinary least squares linear regression to model a continuous business outcome such as weekly user spend from several features,...
Design an Identity Trust Experiment
You are joining an Identity & Trust team at a consumer marketplace. The team wants to launch a new identity-verification badge that appears on seller ...
Explain SHAP and build an ML project
Part A: SHAP 1. What is SHAP (SHapley Additive exPlanations) trying to measure? 2. How do you interpret: - A local SHAP explanation for a single pr...
Should you roll out if NSM decreases?
Scenario You ran an experiment. The north star metric (NSM) is profit per order. Observed results - Average order volume increased in treatment vs con...
Navigate conflicting signals and ambiguous expectations
Behavioral & Leadership Onsite: Changing Expectations, Stakeholder Pushback, Preparation Strategy, and Learning Plan Context You are interviewing for ...
Analyze data duplication effects in linear regression
OLS With Duplicated Observations: Estimator, Variance, and Inference Pitfalls Context: You have the linear model y = Xβ + ε with full-rank X ∈ ℝ^{n×p}...
Lead structured response to accuracy incident
Incident Response Plan: Spike in Incorrect Payments for CA Users Aged 18–24 Scenario Since 00:00 today, the share of incorrect payments for users aged...
Compute expected max/min of n die rolls
You roll a fair six-sided die n times independently. 1) Compute the expected value of the maximum roll. 2) Compute the expected value of the minimum r...
Find the Next Larger Palindrome
Given a positive integer n, return the smallest integer strictly greater than n whose decimal representation is a palindrome. A palindrome reads the s...
Design an ad recommendation and ranking system
You are building an ad recommendation/ranking system for a content feed (e.g., short-form videos). At each feed position, you may show either an organ...
Investigate Falling Successful Orders in LA
DoorDash observes that the number of successful orders per day in the Los Angeles market has declined materially over the last 2 weeks relative to the...