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 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...
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...
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 diff-in-diff and pretrend flag
You are given individual-level observational data for an experiment-like setting with: - period[i] ∈ {0,1}: 0 = pre period, 1 = post period - treatmen...
Evaluate a cold-start rating launch
Uber Eats is considering showing an initial rating for newly onboarded restaurants that have little or no historical review data. This is a two-sided ...
Build a Next-Word Predictor
Implement a simple next-word model over tokenized training sentences. You need to write two functions: 1. train(sentences): receives a list of tokeniz...
Diagnose conversion-rate time series and CTA swap
Part A — Diagnose a conversion/approval-rate time series You are given a monthly time series of credit card approval rate from Jan 2013 to Jan 2015. Y...
How do you choose a classification threshold?
Context You built a binary sentiment classification model (e.g., positive vs. negative) and need to deploy it in a product where actions depend on the...
Build a fair loan classifier
You are given a dataset of loan applicants. Each row represents one loan application and contains applicant attributes, loan attributes, and a binary ...
How do you derive CDF from a PDF?
You are given a continuous random variable \(X\) with probability density function (PDF) \(f_X(x)\). 1. Write the definition of the cumulative distrib...
Answer basic probability and statistics questions
You are given several short, independent probability and statistics questions similar to those in a data / ML screening test. Answer all sub-questions...
Compare XGBoost and LightGBM
In a machine learning interview, explain the key differences between XGBoost and LightGBM for a tabular booking-conversion prediction problem. Your an...
Compute reply-based user metrics in 7 days
You are analyzing discussions on a social platform. Tables all_post - post_id (BIGINT, PK) - post_author_id (BIGINT, FK → user.user_id) - post_creatio...
Optimize Pricing Strategy to Achieve Profitability and Market Growth
Cloud-Service Startup Pricing and Go-To-Market Case A cloud-service startup is reevaluating its pricing and go-to-market strategy while currently oper...
Evaluate Factors Before Replacing Recommendation Model
Evaluate Factors Before Replacing a Recommendation Model A large ads platform has built a new recommendation or ranking model and plans to deprecate t...
Evaluate Impact of New Roblox Homepage Tab
Evaluate the Impact of a New Roblox Homepage Tab Roblox plans to replace an existing homepage tab with a new one. The team needs to measure whether th...
Evaluate Impact of Bicycle Deliveries on Efficiency and Costs
Evaluate Impact of Bicycle Deliveries on Efficiency and Costs A food-delivery marketplace plans to let couriers sign up to deliver by bicycle in addit...
Evaluate Energy One's Transition to Renewable Energy Sources
Evaluate Energy One's Transition to Renewable Energy Sources Energy One is evaluating a move from fossil fuels to renewable power and must analyze fin...
Boost App Installs: Analyze and Experiment with Conversion Funnel
Mobile Web Order to App Install Funnel and Experiments Many users place orders through mobile web but never install the native app. The company wants ...
Assess Success Criteria for Bike-Courier Delivery Launch
Assessing a Bike-Courier Delivery Launch DoorDash plans to launch a bike-courier delivery option and wants to assess whether, where, and how to roll i...