Data Science Interview Prep

Land your dream data science role at Google, Amazon, Microsoft, Meta, Apple, and other top companies. Learn from mock interviews, frameworks, and advice from senior candidates. Practice statistics, experimentation, coding, SQL, machine learning, behavioral interviews, and more.

Top data science interview questions and answers

Coding exercises and AI feedback

Full-length mock interviews & walkthroughs

4.8/5•5,300+ students•Updated Jun 2026

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Interview prep trusted by 1M+ candidates who've landed jobs at

Taught by Data Scientists & Hiring Managers at Google, Amazon, Meta, top startups, and more

Apurvaa SubramaniamData Scientist, Instacart, Amazon

Shreyas LakhtakiaSenior Data Scientist, AI, Stanford, BCG

Angelica C.ML Engineer, Google

Tyler ShangSenior Data Science Manager, Tinder

Joshua BernhardDirector of Data, Intuit, Houzz

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What you'll find in these courses

8 courses

60 hours

Data Scientist Interviews Introduction

3 lessons

1 video

Welcome to Exponent’s Data Science Interview Course!Free

Types of Data Science Roles

The Data Science Interview Loop

Statistics and Experimentation Questions

8 modules

77 lessons

23 videos

Understand what types of statistics questions are asked in data science interviews and what interviewers are looking for. Review fundamental statistics concepts through concise refresher lessons. Learn how to design A/B and hypothesis tests in interviews.

Introduction to Statistics and Experimentation Questions

Rubric for Statistics and Experimentation Questions

How to Answer Data Preprocessing and Quality Questions

Descriptive Statistics

Normalization vs. Standardization

Introduction to Probability QuestionsFree

How to Answer Probability Questions

Probability Concepts

What is a P-value?

Calculate Expected Cost of Coupon Usage

Calculate Conditional Probability (Bayes Theorem)

Calculate Probability of a Fair Coin

Introduction to Regression QuestionsFree

Linear Regression Concepts

Logistic Regression Concepts

How to Answer Regression Questions

Select Input for Modeling When Handling Multicollinearity

Gradient Descent and Model Optimization

Advantages and Limitations of Linear Regression

Modeling Linear Regression

R-Squared, Multicollinearity, and Statistical Tests

Introduction to Hypothesis Tests and Confidence Intervals QuestionsFree

How to Answer Hypothesis Test Questions

How to Calculate Confidence Intervals

Define Confidence Level in Confidence Interval

Introduction to Power Analysis and Impact SizingFree

How to Answer Impact Sizing Questions

How to Answer Power Analysis Questions

Determine Sample Size

Calculate Revenue from New Vertical Expansion

Introduction to Experimentation QuestionsFree

How to Answer A/B Testing Questions

Alternatives to A/B Testing

Design Campaign Experiment and Success Metrics

Design A/B test for New Campaign

Design A/B Testing Alternatives

Design Test for Stories Reaction Feature

Design Test for Driver Matching Algorithm

Increase Sales through A/B Testing

Adjust P-value Threshold

Faster A/B Testing and Statistical Significance

A/B Testing Email Campaign

Analyze A/B Test Results for Checkout

T-test Assumptions and Alternatives

Standard Deviation vs Range

Power vs. Confidence Level

Expectation of Variance

Checking Random Assignment in A/B Testing

What is A/B testing

Statistical Background behind Power

Type I vs. Type II Error

Multiple t-tests

Covariance vs. Correlation

Common Pitfalls of A/B Testing

Explain Confidence Interval

Central Limit Theorem and its Usefulness

Z and T-tests

Hypothesis Testing and p-values

Hypothesis Testing for Coin Flip

Hypothesis Testing for Amazon

Distribution of Daily Minutes on Facebook

Search Distribution

Correlation and Outliers

False Positive Distribution

Biased vs Unbiased Estimator

Statistical Significance vs Practical Significant

Sampling Distribution in Inferential Statistics

Novelty and Primary Effects in Experiments

Non-Normal Distribution

Network Effects in A/B Testing

What is A/B testing and when should it be used?

Verifying Random A/B Testing Groups

Data Communications Questions

2 modules

7 lessons

3 videos

2 hours

Learn how to present and communicate results effectively in any data science or analytics interview round. Understand how to solve ambiguous interview questions through effective communication, specifically for case studies, past project presentations, and take-home assignments.

How to Present Past Projects

Present a Past Project 1

Present a Past Project 2

Present a Past Project 3

Introduction to the Take-home Assignment Free

How to Create a Take-home for Defined Tasks

How to Create a Take-home for Open-ended Tasks

Python Coding Questions for Data Scientists

2 modules

18 lessons

2 videos

Master Python coding interviews focused on data science by exploring advanced data manipulation with Pandas and conducting statistical analysis and experiments. Gain proficiency in handling and transforming datasets, performing thorough statistical tests, and designing experiments with Python. Perfect for those looking to excel in technical interviews that assess data handling and analytical skills.

Lowest Earning EmployeesEasy

Unsold ProductsEasy

SQL Interviews

9 modules

98 lessons

6 videos

Prepare for SQL interviews by practicing syntax basics, aggregations, and window functions. Learn how to manipulate data, write complex queries, and analyze information from diverse data sets.

Introduction to SQL and Its HistoryFree

How to Answer SQL Interview Questions

Relationships and Relational Database Concepts

How to Prep SQL Interviews FastFree

SQL Interview PatternsFree

SQL Interview Test QuestionsFree

Joins & Duplicate ControlFree

Window Functions EssentialsFree

Grouping, Having, Conditional Aggregation & NULL-Safe MetricsFree

Subqueries & CTEsFree

Dates & BucketingFree

How to Perform in a SQL Interview Free

Basic SQL Syntax

The WHERE Clause

Logical operators: AND, OR, NOT

Querying Missing Values with IS NULL and IS NOT NULL

Sorting data with ORDER BY

Using LIMIT and OFFSET

IN and BETWEEN

Introduction to SQL Aggregations

GROUP BY and HAVING

Counting with COUNT and COUNT(DISTINCT)

SUM

Calculating Average, Min, and Max with SQL

Conditional values with CASE WHEN ... ELSE

Working with Date and Time: DATE_TRUNC, DATEDIFF, and more

Subqueries and Derived tables

Common Table Expressions (CTEs)

Introduction to Window Functions

Window functions: RANK and DENSE RANK

Window functions: ROW_NUMBER

Window functions: LAG

Introduction to SQL Practice QuestionsFree

Top Earning EmployeesEasy

Monthly Post Success AnalysisFreeEasy

High Volume Low SuccessFreeEasy

Tree NodeEasy

Marketing Campaign DurationFreeEasy

Find Average Purchase ValueFreeEasy

Survey SamplingFreeEasy

Items on SaleEasy

Reddit UsersEasy

Lyft Ride RequestsEasy

E-commerce: Units Ordered Yesterday Easy

E-commerce: Units Ordered Last WeekEasy

E-commerce: Earliest Order by CustomerEasy

Sales by Customer CityMedium

Most Recent TransactionMedium

Calculate Test ScoresMedium

Project BudgetsFreeMedium

Instagram LikesMedium

Employee EarningsMedium

Post Success By InterfaceFreeMedium

Post Success By Age GroupFreeMedium

Find Campaign PurchasesFreeMedium

Find Revenue by DepartmentMedium

Find Customers by DepartmentMedium

Find Second Highest OrderMedium

Find Conversion RatesFreeMedium

Find Customer Lifetime Value (LTV)Medium

Marketing Channel AttributionMedium

Analyze Monthly Customer Transactions

Sales ReportMedium

Monthly Sales ReportMedium

Top Customer by OrdersMedium

TV Show Watch TimeMedium

Nth Ranked PlayerMedium

Number of Direct ReportsMedium

Fraudulent TransactionsMedium

EPA Temperature MonitoringMedium

Video Game MatchmakingMedium

Walmart Inventory StatusMedium

Unique Chat ConversationsMedium

Netflix Genre RatingsFreeMedium

Remove Duplicate EmailsMedium

Consecutive LoginsMedium

E-commerce: Total Orders by CategoryMedium

Total Transaction VolumeFreeHard

Top Salaries by DepartmentFreeHard

Employee HierarchyFreeHard

Post Success After FailureHard

Find Top Customer by YearHard

Find Monthly Revenue GrowthFreeHard

Initial Contact AttributionHard

Ranking Salary DeviationsHard

Game LeaderboardHard

Amazon Order StatusFreeHard

Duolingo LeaderboardsFreeHard

Validate Bitcoin TransactionsHard

E-commerce: Second Earliest OrderFreeHard

SQL Stored Procedures

Product Sense and Case Studies

3 modules

32 lessons

13 videos

Product sense is about understanding user needs and designing intuitive, high-impact solutions. In interviews, it’s tested through questions that assess your creativity, empathy, and ability to prioritize. Case studies evaluate your structured thinking—how you break down ambiguous problems and reason through them like a strategic business partner.

Introduction to Analytical QuestionsFree

How to Answer A/B Testing Questions

How to Answer Metrics Questions

Rubric for Analytical Interviews

Pick YouTube's Key Metrics

A/B Test Google's Homepage

Top 3 Variables of Uber's Passenger Pickup

Instagram Reels Success Metrics

LinkedIn Events Success Metrics

A/B Test Google Maps

Measure Success for Slack Connect

Measure Success for Instagram Discovery

A/B Testing Email Campaign

Improving Facebook’s DAU

Diagnosing Instagram DAU Drop

More Analytical/Execution Practice

Introduction to Product Design Questions

How to Answer Product Design Questions

Design Facebook MoviesFree

Design Audio Product for Meta

Introduction to the Case Study InterviewFree

How to Answer Case Study Interview Questions

Investigate Sudden Viewer Drop at Meta

Integrate Data in Netflix License Renewal

Balance Ads vs Follower Instagram Posts

Onsite Technical Round: Combination of SQL, Statistics, and Case Study

Improve Snap Camera Speed

Instagram Messaging with 3rd Party

Facebook Video for Individuals with Hearing Disabilities

Evaluating Facebook’s Emotion Scale

Identifying Conversations in Comments

Measuring Product-Market Fit for Meta Video

ML Coding Questions for Data Scientists

2 modules

10 lessons

7 videos

Master coding interviews that assess your knowledge of ML frameworks. Learn how to implement core ML components. Particularly important for DS candidates applying for roles in machine learning and algorithms.

Introduction to ML Coding InterviewsFree

How to Answer ML Coding Interview Questions

Rubric for ML Coding Interviews

Implement the KNN AlgorithmEasy

Implement K-Means Clustering Easy

Optimal Value of K in K-Means

Implement a 2D Convolutional FilterMedium

Predict User App DeletionHard

Predict Harmful TextHard

Split Dataset for Training, Evaluation, Testing

ML Concepts Questions for Data Scientists

3 modules

29 lessons

8 videos

Learn best practices for answering ML concepts questions. Particularly important for data science candidates applying for roles in machine learning and algorithms.

Introduction to ML Concepts Interviews

How to Answer ML Data Handling Questions

How to Answer ML Model Questions

How to Answer ML Evaluation Questions

How to Answer ML Production Questions

Rubric for ML Concepts Interviews

ML Interviews Glossary

Linear RegressionFree

Density-Based Spatial Clustering (DBSCAN)

Supervised Model Evaluation

Describe Linear Regression

Explain the Bias-Variance Tradeoff

Explain “Training" and “Testing” Data

Discuss Batch, Mini-Batch, Stochastic Gradient Descent

Explain Feature Scaling and Normalization

Explain Classification vs Regression

Identify When Model Needs Refresh

Handle an Exploding Gradient

Build Fraud Detection Model

Describe How Decision Trees are Created

Measure Algorithm Success

Compare Forecast Models to Other ML Models

Build Recommendation System for Online Courses

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Question database and community answers Get full access to our database of 3,000+ verified interview questions and browse by company, role, or interview stage. Post your answers and get community feedback.

Access all our company interview guides We'll walk you step-by-step through every part of the interview process, from the recruiting phone screen through the final round.

Join our members-only Slack community Connect with your peers in our 25,000-member strong Slack community. Ask questions, practice interviews, and make connections at top tech companies.

Mock interviews with AI and peers Practice real interview questions with unlimited mock interviews, including early access to our new AI interviewer.

Frequently asked questions

: With a paid monthly or annual membership, you’ll get:

Full access to our PM interview course and 100+ other interview prep courses and modules.

Hundreds of real PM interview questions, answers, and walkthroughs

Self-paced video lessons with expert interview answer frameworks

Access to PM interview rubrics and sample answers for common interview types

Unlimited access to peer-to-peer mock interviews for product sense, behavioral, and more.

Access to AI tools for mock interview feedback

A complete library of company-specific PM interview guides

Membership in our private Slack community
: Yes! You can purchase coaching for interview prep and career coaching by visiting https://www.tryexponent.com/coaching.

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Data Science Interview Prep

Taught by Data Scientists & Hiring Managers at Google, Amazon, Meta, top startups, and more

What people like about these courses

Data Scientist Interviews Introduction

Statistics and Experimentation Questions

Data Communications Questions

Python Coding Questions for Data Scientists

SQL Interviews

Product Sense and Case Studies

ML Coding Questions for Data Scientists

ML Concepts Questions for Data Scientists

Get these courses, plus everything Exponent has to offer

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