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Data Scientist Interview Questions

Data Scientist Interview Questions

Practice 3,024 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.

Questions
3.0k
Companies
145
Updated
05.27.2026
3.0k Questions 145 Companies05.27.2026
PLTCHK testimonial
PLTCHK

"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"

_The_TaNk_ testimonial
_The_TaNk_

"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"

Chris testimonial
ChrisSenior SWE, LinkedIn

"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."

sleepy33 testimonial
sleepy33

"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."

Jake testimonial
JakeSenior ML Engineer, Lyft

"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."

nuggetlord testimonial
nuggetlord

"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."

Carlos testimonial
CarlosFull Stack, Shopify

"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."

boba.tea.vibes testimonial
boba.tea.vibes

"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."

Andy testimonial
AndySWE-II, Google

"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."

couchpotato99 testimonial
couchpotato99

"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."

Shruti testimonial
ShrutiData Engineer, Salesforce

"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."

midnightramen testimonial
midnightramen

"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."

Bianca testimonial
BiancaFrontend Eng, Figma

"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."

tambrahm007 testimonial
tambrahm007

"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."

toa testimonial
toa

"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."

PLTCHK testimonial
PLTCHK

"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"

_The_TaNk_ testimonial
_The_TaNk_

"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"

Chris testimonial
ChrisSenior SWE, LinkedIn

"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."

sleepy33 testimonial
sleepy33

"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."

Jake testimonial
JakeSenior ML Engineer, Lyft

"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."

nuggetlord testimonial
nuggetlord

"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."

Carlos testimonial
CarlosFull Stack, Shopify

"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."

boba.tea.vibes testimonial
boba.tea.vibes

"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."

Andy testimonial
AndySWE-II, Google

"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."

couchpotato99 testimonial
couchpotato99

"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."

Shruti testimonial
ShrutiData Engineer, Salesforce

"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."

midnightramen testimonial
midnightramen

"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."

Bianca testimonial
BiancaFrontend Eng, Figma

"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."

tambrahm007 testimonial
tambrahm007

"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."

toa testimonial
toa

"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."

Showing 20 results
Role
Uber logo
Uber
Medium
Data Scientist Locked

Evaluate Promotions for Uber Eats Users

Uber Eats wants to send promotions or coupons to users. Design an experiment and analysis plan to evaluate whether the promotion is effective. Address...

Machine Learning
47
0
358 people solved
Apr 30, 2026
Meta logo
Meta
Medium
Data Scientist

Estimate ads ranking revenue impact

You are the data scientist for an ads ranking team. The team has built a new ranking algorithm for feed ads. The new model changes the ordering of ads...

Analytics & Experimentation
24
0
165 people solved
Apr 30, 2026
LinkedIn logo
LinkedIn
Medium
Data Scientist

Explain Logistic Regression, Backprop, and Adam

Answer the following machine learning fundamentals questions: 1. Logistic regression - Explain how logistic regression works for binary classificat...

Machine Learning
123
0
930 people solved
Apr 5, 2026
DoorDash logo
DoorDash
Hard
Data Scientist

Evaluate Biker Feature Success

DoorDash is considering launching a Biker Mode feature for Dashers who deliver by bicycle. The feature may help bicycle Dashers identify suitable shor...

Analytics & Experimentation
12
0
118 people solved
Apr 25, 2026
Uber logo
Uber
Medium
Data Scientist Locked

Design Uber Eats Restaurant Recommendations

Design a restaurant recommendation system for the Uber Eats home page. A user opens the Uber Eats app and should see a ranked feed of restaurants avai...

ML System Design
12
0
101 people solved
Apr 30, 2026
Amazon logo
Amazon
Easy
Data Scientist

Answer Amazon Leadership Principle Scenarios

In an Amazon Data Scientist intern virtual interview, answer behavioral questions using the STAR method and tie each story to Amazon Leadership Princi...

Behavioral & Leadership
15
0
106 people solved
Apr 3, 2026
Capital One logo
Capital One
Medium
Data Scientist

Analyze Subscription, Insurance, App, and Card Cases

You are in a data science and product analytics power-day interview. The following four subcases are independent. For each one, state your assumptions...

Analytics & Experimentation
6
0
103 people solved
Apr 12, 2026
Meta logo
Meta
Medium
Data Scientist

Measure scheduled posts feature success

Facebook is considering launching a new feature that allows users to schedule a post to be published at a future time. The product hypothesis is that ...

Analytics & Experimentation
4
0
52 people solved
Apr 30, 2026
Amazon logo
Amazon
Easy
Data Scientist

Evaluate NLP Classification Models

You are interviewing for a Data Scientist internship and discussing an NLP classification project, such as classifying customer messages, search queri...

Machine Learning
7
0
89 people solved
Apr 3, 2026
Instacart logo
Instacart
Hard
Data Scientist

Interpret and Regularize Regression Models

You are building and interpreting regression models for a product dataset. The outcome variable is a continuous user-level metric such as spend, sessi...

Statistics & Math
2
0
24 people solved
May 3, 2026
Meta logo
Meta
Medium
Data Scientist

Count unconnected posts and reactions

You are analyzing a newly launched feed feature intended to improve engagement by showing more unconnected content. Assume the following tables: - pos...

Data Manipulation (SQL/Python)
20
2
189 people solved
Apr 5, 2026
Meta logo
Meta
Hard
Data Scientist

Write SQL for reply-based recipient metrics

You work on a social product and are given two tables. Assumptions (use these unless you state otherwise): - All timestamps are in UTC. - A “reply” is...

Data Manipulation (SQL/Python)
46
2
428 people solved
Mar 5, 2026
J.P. Morgan logo
J.P. Morgan
Medium
Data Scientist

Explain Core ML Concepts

You are interviewing for a senior AI/ML-oriented data science role at a financial institution. Answer the following foundational machine learning ques...

Machine Learning
5
0
37 people solved
Apr 24, 2026
Pinterest logo
Pinterest
Medium
Data Scientist Locked

How would you evaluate a carousel launch?

You are the data scientist supporting Pinterest's home feed. Product wants to add a horizontally scrollable carousel at the top of the app, similar to...

Analytics & Experimentation
22
0
146 people solved
Mar 10, 2026
Instacart logo
Instacart
Hard
Data Scientist

Design and Interpret an A/B Test

You are evaluating a product experiment with a control group and two treatment variants, v1 and v2. The primary metric is a user-level conversion rate...

Analytics & Experimentation
2
0
16 people solved
May 3, 2026
J.P. Morgan logo
J.P. Morgan
Medium
Data Scientist

Implement Integer Square Root

Given a non-negative integer x, implement sqrt(x) and return the integer part of its square root, i.e., floor(sqrt(x)). Requirements: - Do not use a b...

Coding & Algorithms
4
0
27 people solved
Apr 24, 2026
OpenAI logo
OpenAI
Hard
Data Scientist

Write SQL for repeat churn

Write a SQL query to measure the performance of a free-month promotion experiment. Assume experiment_users already contains only users who were eligib...

Data Manipulation (SQL/Python)
33
0
326 people solved
Feb 3, 2026
Squarepoint logo
Squarepoint
Medium
Data Scientist

Solve Probability and Statistics Questions

Answer the following probability, statistics, and modeling questions. Part 1: Linear regression and OLS Explain ordinary least squares linear regressi...

Machine Learning
0
0
12 people solved
May 3, 2026
Two Sigma logo
Two Sigma
Medium
Data Scientist

Analyze Temperatures and Update Regression

You are given historical daily temperature data for New York City and several nearby towns. Each row contains a date, the NYC temperature, and the tem...

Machine Learning
2
0
24 people solved
Apr 21, 2026
Zoox logo
Zoox
Easy
Data Scientist

Solve estimation and probability brainteasers

Answer the following independent brainteaser questions. State any assumptions you need. 1) Tile a floor: A floor is 15 ft × 20 ft. You will cover it w...

Statistics & Math
47
0
623 people solved
Nov 13, 2025
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Frequently Asked Questions

How difficult are Data Scientist interview questions at top tech and fintech companies in 2026?
Difficulty varies by level and team but is generally medium-to-high for product-facing roles at large tech firms and can be higher for research or machine-learning-specialist tracks. Expect analytics-and-expansion questions that emphasize SQL, experiments, and product metrics at companies like Meta and TikTok, while firms such as Capital One may add domain- and case-style problems that simulate business tradeoffs. Senior roles test end-to-end judgment: model choices, deployment risks, and influence. You should be comfortable with clear assumptions, tradeoff discussions, and writing concise queries or short Python snippets under time pressure.
What does the typical Data Scientist interview process look like and where do these roles most often appear?
Most companies follow a multi-stage process: an initial recruiter screen, one or more technical screens that blend SQL or Python with a metrics or A/B case, and a final interview loop covering analytics, statistics/experimentation, modeling, and behavioral leadership. Product-analytics roles are common at Meta, Google, Amazon, and TikTok, emphasizing funnel and experiment diagnostics; Capital One and other financial firms often include case-style questions that mirror customer or risk decisions. Expect 3–6 interviews in the loop, and be prepared to explain tradeoffs and business impact alongside technical answers.
How should I structure my preparation timeline for 8–12 weeks before Data Scientist interviews?
Start by diagnosing weaknesses: spend the first two weeks consolidating SQL fundamentals and pandas-based data manipulation, then dedicate the next three weeks to statistics and experiments, including hypothesis tests, CIs, and power reasoning. Use weeks 6–8 to practice product-analytics cases and mock interviews focused on funnel and A/B troubleshooting, and reserve the final 2–3 weeks for modeling basics, short Python coding practice, and refining behavioral stories with measurable impact. Regular timed practice on real interview prompts and loop-style mocks yields the best transfer to actual interviews.
What core technical subtopics should I master to perform well as a Data Scientist in interviews?
Focus on five high-leverage areas: SQL and data-frame manipulation (joins, group-bys, windows, CTEs), statistics and experimentation (A/B design, power, bias, confounding), feature engineering and model evaluation (precision/recall, calibration, business metrics), Python for quick analysis and reproducible code, and product analytics thinking (funnels, segmentation, metric definition). Additionally, understand basic deployment and monitoring tradeoffs for production models and be able to discuss assumptions, data quality issues, and how your choice of metric changes conclusions.
What standout tips and common pitfalls should I keep in mind for Data Scientist interviews?
Start answers by clarifying the question and stating assumptions, then walk through your approach before diving into calculations or queries. Tell a concise data-driven story that quantifies impact and tradeoffs. Practice writing clean SQL and short Python snippets under time limits, and rehearse experiment diagnosis aloud. Avoid common pitfalls: failing to define metrics precisely, ignoring segment effects or missing-data biases, overfitting toy models, and giving unfounded causal claims. For behavioral rounds, focus on influence and measurable outcomes rather than raw technical depth alone.
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