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."
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"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."
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"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."
Answer ambiguity and PM disagreement behavioral questions
Behavioral questions 1) Describe a time you worked on a problem with high ambiguity (unclear goals, incomplete data, shifting requirements). What did ...
Design bot detection and evaluate trade-offs
Bot-Detection System Design for Comment Activity Context You are designing and evaluating a machine learning system to detect automated (bot) comment ...
Design a robust traffic forecasting pipeline
Forecasting Daily Amazon Retail Traffic: End-to-End Design You are given 5 years of daily Amazon retail site traffic counts. Design an end-to-end fore...
Design a better water bottle and test it
Propose 10 mutually exclusive design improvements for a commuter-focused reusable water bottle (e.g., insulation, grip, cap mechanism, filter, materia...
Build a model to infer home vs office vs public
You must infer whether a Facebook session’s network context is home, office, or public venue to inform Portal targeting. Constraints: IPs may be share...
Compute sample size and test duration
You will run a two-arm A/B test on a signup funnel. Given: baseline conversion p0 = 4.0%; you care about detecting a 10% relative uplift (p1 = 4.4%); ...
Set membership fee under investment constraints
Streaming membership pricing vs. content investment Context You are designing a monthly membership for a streaming service. Producing original shows i...
Graph WTP vs content and explain cap
Willingness-to-Pay (WTP) vs. Content Quantity Context Assume the number of available shows is a nonnegative quantity S (S ≥ 0). A customer's maximum w...
Build and evaluate illegal-video classifier
End-to-End ML System Design: Flag Illegal YouTube Videos You are tasked with designing a production ML system to detect and triage potentially illegal...
Find companies similar to a given client
System Design: Retrieve Top-20 Most Similar Companies for Sales Prospecting You are given an anchor client (e.g., The Coca‑Cola Company). Design a sys...
Estimate population singletons from a 10% log
A daily search log has one row per query string. You draw a 10% simple random sample of rows without replacement. Define a “unique query” (singleton) ...
Estimate b when features exceed samples
Consider the linear model y = Xb + ε with X ∈ R^{n×(m+1)} including an intercept. a) Derive the OLS estimator b̂ = (XᵀX)^{-1}Xᵀy, stating the rank con...
Estimate unbiased ad scores with many reviewers
You have 1,000 ads and 100 reviewers; each reviewer rates 100 ads on a 1–10 scale with incomplete overlap. Specify a mixed-effects model to estimate l...
Generate binomial matrix and column-normalize
Using Python with NumPy, generate a 100×100 matrix of Binomial(n = 10, p = 0.3) draws with a fixed random seed, then normalize each column so it sums ...
Handle p≈n linear regression with L1
You must fit linear regression with p = 500 predictors and n = 600 observations. What failure modes do you expect and why does OLS overfit when p is c...
Run a clean A/B test for recommendations
You must run an A/B test to evaluate the new hashtag recommender starting on 2025‑09‑01. 1) Define the randomization unit (user/session/impression) an...
Demonstrate invent-and-simplify and customer communication
Behavioral: Two STAR Stories (Data Scientist, Technical Screen) Provide two concise STAR stories that demonstrate your ability to invent/simplify and ...
Implement an LRU cache with O(1) ops
Design and code an LRU cache supporting get(key) and put(key, value) in O(1) average time with capacity N. Specify your data structures, handle update...
Choose evaluation metrics for imbalanced risk model
Cost-Sensitive Fraud Detection: Thresholding, Metrics, and Calibration Assume a binary fraud classifier outputs calibrated probabilities p = P(y=1|x)....
Build referral chains and detect cycles
You are given a directed referral graph where each user may have at most one referrer. Input file 'referrals.csv' has columns: user_id (INT), referred...