Data scientist interview preparation, round by round
Data science interviews test statistics, ML theory, SQL on product data and A/B test design. Product companies often add an ML system design round.
24 resources · 17 free · plus 23 for every role · Links checked 15 October 2026 · How we pick
Change role
- Software engineer 54 resources
- Backend developer 45 resources
- Frontend developer 37 resources
- Full stack developer 43 resources
- Mobile developer 19 resources
- DevOps and SRE 24 resources
- Data engineer 23 resources
- Data analyst 21 resources
- Data scientist 24 resources
- ML engineer 31 resources
- AI engineer 27 resources
- QA and SDET 12 resources
Start here
Three resources, in this order. Everything below is for going deeper on one round.
- Introduction to Machine Learning Interviews (Chip Huyen)
Book · Free
Read the early chapters to see which rounds a data science interview has, then use its question list to find your gaps.
- StatQuest with Josh Starmer
YouTube channel · Free
Fill the statistics and ML gaps the question list showed. Watch only the topics you could not explain out loud.
- DataLemur
Practice site · Free tier
Practise SQL and probability on product-style tables, the way data science interviews ask them. Start with the free questions.
Nothing matches these filters. Use Show all to see every resource again.
ML theory and statistics 13 resources
Statistics, probability, A/B tests, ML algorithms and how to judge a model
Introduction to Machine Learning Interviews (Chip Huyen)
Book · huyenchip.com
A free online book that explains ML roles, hiring loops and offers, then lists 200+ maths, CS and ML questions by difficulty, about a tenth with written answers.
Best for a first read for any ML or data science candidate who wants to know what each round tests
StatQuest with Josh Starmer
YouTube channel · youtube.com
Short, step-by-step video explanations of statistics, classic ML algorithms and neural networks, built for filling gaps before a theory round.
Best for revisiting a concept you can't yet explain cleanly, such as p-values or gradient boosting
DataLemur
Practice site · datalemur.com
Company-tagged SQL problems on realistic product-analytics tables, plus probability, statistics, ML and Python questions and a free SQL tutorial.
Best for analyst and data science candidates practising the business-style SQL that big-tech screens use
Also in SQL, A/B tests, metrics and product sense questions
Data Science Interviews (Alexey Grigorev)
GitHub repo · alexeygrigorev/data-science-interviews
Community-written answers to common data science theory and technical questions, from linear models, trees and metrics to SQL and Python, plus probability problems.
Best for quick revision of theory and SQL basics before a data science phone screen
Also in SQL, A/B tests, metrics and product sense questions
An Introduction to Statistical Learning (ISLR / ISLP)
Book · statlearning.com
The standard introductory text on regression, classification, resampling, tree methods and unsupervised learning, with R and Python editions free from the authors.
Best for the classical-ML fundamentals that data science interviews keep probing
AIMLInterviews (formerly Machine-Learning-Interviews)
GitHub repo · alirezadir/AIMLInterviews
A big-tech ML interview guide arranged by round: coding, ML coding, ML breadth including GenAI and agents, ML system design and behavioral, from the author's own loops.
Best for planning FAANG-style ML engineer or applied scientist prep one round at a time
Also in ML system design, Coding and DSA
Machine Learning Q and AI (Sebastian Raschka)
Book · sebastianraschka.com
Thirty short chapters, each built around one question on deep learning, vision, NLP and LLMs, deployment or evaluation, that work as practice for 'explain X' rounds.
Best for mid-level ML and AI candidates who want depth on conceptual follow-up questions
A/B Testing by Google (Udacity)
Course · udacity.com
A short free course by Google data scientists on running experiments: choosing and checking metrics, sizing and designing a test, ethics, and analysing results.
Best for product data science loops that include an experimentation or A/B testing round
Also in A/B tests, metrics and product sense questions
Krish Naik (YouTube)
YouTube channel · youtube.com
An Indian educator's channel with data science and ML interview-question playlists, recorded mock interviews, end-to-end projects and GenAI tutorials in English and Hindi.
Best for Indian freshers and career switchers moving into data science, ML or GenAI
Emma Ding (Data Interview Pro)
YouTube channel · youtube.com
A former Airbnb data scientist's channel that walks through product-sense cases, metric design, A/B testing, statistics and SQL interview questions.
Best for product-analytics data science interviews built around metrics, experiments and cases
Also in SQL
Harvard Stat 110: Probability (Blitzstein & Hwang)
Course · stat110.hsites.harvard.edu
Harvard's probability course with recorded lectures, topic-wise practice problems with full solutions, and a free online edition of the Blitzstein-Hwang textbook.
Best for the probability puzzles and distribution questions in data science and ML screens
Deep-ML
Practice site · deep-ml.com
A LeetCode-style judge where you implement ML maths and models in Python, from linear algebra and optimisers to attention and a small GPT, against test cases.
Best for the ML coding round, where you write algorithms from scratch in NumPy or PyTorch
StrataScratch
Practice site · stratascratch.com
A large bank of SQL, Python, statistics and ML questions reported from real data interviews, filterable by company, with dialect choice and community solutions.
Best for volume and company-specific SQL and pandas practice once your SQL basics are solid
Also in SQL, A/B tests, metrics and product sense questions
SQL 5 resources
Writing queries with joins, grouping and window functions on realistic tables
roadmap.sh interview question guides
Website · roadmap.sh
Free topic-by-topic Q&A guides with quiz cards, from backend, frontend, Java, Spring Boot, Go, Python and Node.js to SQL, Kubernetes, DevOps and data analysis.
Best for quick topic-wise revision of language, framework and tool questions before an interview
Also in A/B tests, metrics and product sense questions
codebasics (YouTube)
YouTube channel · youtube.com
Dhaval Patel's channel of free Python, SQL, Power BI and Excel tutorials, end-to-end analytics projects, and data career and interview advice.
Best for Indian analyst candidates who want tool tutorials, project ideas and interview tips in one place
Also in A/B tests, metrics and product sense questions
LeetCode SQL 50 study plan
Practice site · leetcode.com
Fifty judged SQL problems in seven groups, from selects and joins to aggregates, subqueries and string functions, mostly easy, as a first structured pass.
Best for a first structured set of SQL interview problems for any data or backend role
Aced Practice (formerly Exponent; Pramp moved here)
Practice site · aced.io
Free peer mock interviews where you pair with another candidate and take turns as interviewer, in DSA, system design, behavioral, SQL, data science, ML and frontend.
Best for regular, cheap live practice and a feel for the interviewer's side of the table
Also in Coding and DSA
LeetCode
Practice site · leetcode.com
The default site for interview-style coding practice: thousands of problems, free study plans such as Top Interview 150 and SQL 50, and weekly contests.
Best for daily practice and timed contests (Premium mainly adds company-tagged lists)
Also in Coding and DSA
A/B tests, metrics and product sense questions 1 resource
Questions on your stack: languages, frameworks, cloud, testing and data tools
MLOps Zoomcamp (DataTalks.Club)
Course · DataTalksClub/mlops-zoomcamp
A free cohort-based course on experiment tracking, orchestration, model deployment and monitoring, ending in a project you can walk interviewers through.
Best for data scientists moving into ML engineering who need hands-on MLOps experience
Also in ML system design
ML system design 4 resources
Designing ML systems end to end: data, training, serving and monitoring
Evidently AI ML & LLM System Design Case Studies
Website · evidentlyai.com
An open index of about 800 company write-ups on how real teams built recommenders, fraud and search systems and LLM, RAG and agent products, filterable by industry.
Best for collecting real design patterns to cite in ML and GenAI system design rounds
Designing Machine Learning Systems (Chip Huyen)
Book · chiphuyen/dmls-book
The best-known book on production ML; the linked companion repo has free chapter summaries, an ML refresher and MLOps tool notes, while the book itself is paid.
Best for mid and senior ML engineers preparing for open-ended ML system design rounds
Machine Learning System Design Interview (Aminian & Xu, ByteByteGo)
Book · bytebytego.com
Ten worked ML design problems, including visual search, harmful-content detection, video recommendation, ad click prediction and people-you-may-know, on one framework.
Best for rehearsing the standard recommendation, ranking and search design questions
Stanford CS329S: Machine Learning Systems Design
Course · stanford-cs329s.github.io
Stanford's 2022 ML systems design course, with every lecture's notes and slides public, covering data engineering, features, deployment, monitoring and distribution shift.
Best for a free, structured base for ML system design before (or instead of) the paid book
Coding and DSA 1 resource
Solving problems with data structures and algorithms, and explaining your approach
Amazon - How We Hire (role-specific interview prep)
Official guide · amazon.jobs
Amazon's hiring hub, explaining each stage from application to the final loop, with role-specific prep pages for SDE, front-end, BI engineer and scientist roles.
Best for finding out what Amazon tests for your role and level, and how its loop works
Same for every role
Behavioral rounds, resumes, pay and company guides do not change with the job. These 23 live on the interview resources hub.
Behavioral and HR
- GeeksforGeeks - HR interview questions
- Microsoft Careers - Interview tips
- MIT CAPD - The STAR method for behavioral interviews
- Tech Interview Handbook - Behavioral interviews
- reverse-interview
- Amazon Leadership Principles
- Google Careers - Interview tips
- Jeff H Sipe - Practice Interviews (YouTube)
- A Life Engineered (Steve Huynh, YouTube)
Practice and communities
Resume, companies and offers
- Tech Interview Handbook - Software engineer resume guide
- Reactive Resume
- Jake's Resume (LaTeX template on Overleaf)
- Hiring Without Whiteboards
- r/developersIndia Community Wiki
- AmbitionBox
- Anthropic - Candidate AI guidance
- Haseeb Qureshi - Ten rules for negotiating a job offer
- Thoughtworks India - AI policy for recruitment
- Levels.fyi - Software engineer pay in India
- r/EngineeringResumes wiki
From the team that keeps this list
Helpwing is a desktop app for interviews where AI help is allowed: it hears the question and drafts an answer from your resume. It is not for online assessments or tests.