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."
Explain Bayes’ Theorem and P-Value in Decision-Making
Explain Bayes’ Theorem and P-Value in Decision-Making Statistics Fundamentals: Bayes' Theorem and p-Values Context Stakeholders want clear, decision-f...
Determine Value of Prioritizing Accounts by Unread Notifications
Determine Value of Prioritizing Accounts by Unread Notifications Feature Validation: Ordering Multiple Accounts by Unread Notifications Context Users ...
Calculate Posterior Fraud Probability Using Bayes' Theorem
Calculate Posterior Fraud Probability Using Bayes' Theorem Posterior Fraud Probability After a Flag Context You operate a fraud detection system that ...
Define Success with Contact Syncing for Growth and Evaluation
Define Success with Contact Syncing for Growth and Evaluation Using "% of users with contacts synced" as a growth driver Context You are a data scient...
Resolve Conflicts Between Data Findings and Team Opinions
Resolve Conflicts Between Data Findings and Team Opinions Behavioral Scenario: Resolving Conflicts Between Data Findings and Team Beliefs Scenario You...
Investigate Causes of Increased Driver Wait Time
Investigate Causes of Increased Driver Wait Time Scenario DoorDash observed that driver (Dasher) wait time at restaurants spiked last week versus the ...
Count Article Types Viewed
Count Article Types Viewed You are given article view events and article metadata. Table 1: article_views — one row per article view event. | Column |...
How to analyze Simpson's paradox
A marketing team wants to evaluate a new email campaign. Two email versions, A and B, were tested over two weeks in two cities: San Francisco and New ...
Analyze profits under random walk and Brownian motion
Analyze profits under random walk and Brownian motion Random-Walk Trading Rules: Expectation and Variance Setup - Let (S_t) be a simple random walk fo...
Explain unsupervised fraud and evaluation
Explain unsupervised fraud and evaluation Unsupervised Fraud Detection: Methods, When to Use Them, and How to Evaluate Without Reliable Labels Context...
Write conditional aggregates with CASE WHEN
Write conditional aggregates with CASE WHEN Write a query that produces conditional aggregates using CASE WHEN (e.g., counts of approved vs declined t...
Resolve Simpson’s paradox in A/B email test
A marketing team tests a new email campaign. They run an experiment for two weeks in two cities (SF and NY) comparing Email A vs Email B. They observe...
Choose better bank queue and describe distributions
You are interviewing for a data role and are asked several probability/distribution questions. 1) Bank queue choice (queueing intuition) A bank has 5 ...
Solve three algorithmic tasks in Python
You are given 120 minutes to implement three independent algorithmic tasks in Python. Each task specifies the required input/output behavior, the cons...
Compute Cohort Retention Rate
You are given two tables: - users(user_id BIGINT, signup_ts TIMESTAMP) — one row per user. - user_activity(user_id BIGINT, activity_ts TIMESTAMP, even...
Implement KNN from Scratch
Implement a k-nearest neighbors (KNN) classifier from scratch in Python without using scikit-learn's KNN implementation. Given training features X_tra...
Find top-paid employee per department
Given the following tables: 1) employees - employee_id INT PRIMARY KEY - employee_name VARCHAR 2) employee_department - employee_id INT - department_i...
Evaluate Notification-Based Account Ranking
A product allows users to switch among multiple accounts. Today, the account switcher ranks accounts by most recent visit. The product team wants to c...
Rank features using logistic regression coefficients
You are given a binary classification dataset: - X: a 2D array of shape (n_samples, n_features) containing numeric features - y: a 1D binary array of ...
Compute A/B test sample size and Bayes posterior
You are working through two short, self-contained statistics tasks that appear together in an online assessment for a Data Scientist role. The tasks a...