Today we’re looking at 8 data science interview books to help you prepare for – and ace! – your data science interview.
You’ll discover their:
- major topics
- skill level
And much more.
Some of these data science interview books focus exclusively on interview topics and specific questions.
…While others cover more general data science topics any aspiring data scientist will likely need to know at an interview.
Let’s crack into them.
This post contains affiliate links. I may receive compensation if you buy something. Read my disclosure for more details.
TLDR: Data Science Interview Books
🔥 Best Overall 🔥
Ace the Data Science Interview
💸 Best Value 💸
Be the Outlier: How to Ace Data Science Interviews
Data Science Interview Books
➡️ Ace the Data Science Interview is possibly one of the overall best data science interview books.
You’ll find 201 data science questions asked at actual FAANG interviews.
For each question, you’ll find step-by-step solution walkthroughs.
The questions cover the most frequently-tested topics in data interviews such as:
✅ A/B testing
✅ database design
✅ machine learning
You’ll also find tips to make your resume stand out, create killer portfolio projects, and discover ways to nail your behavioral interview.
What data scientists are saying about Ace the Data Science Interview:
🚨 Ideal for: data scientists approaching the interview stage
💥 Major topics: modeling, machine learning, probability
Be the Outlier by Shrilata Murthy is specifically designed to help you ace your data science interview. 🦢
You’ll examine three key components of data science interviews.
First you’ll look at the technical portion. This is where you’ll find questions on:
- machine learning
Then you’ll learn how to showcase your experience with data science. This includes projects you’ve worked on and behavioral interview questions.
💡 The behavioral interview is where you exhibit your soft skills and culture fit. Some argue it’s just as important as the technical interview.
Next, you’ll learn how to create a killer data science resume and portfolio.
Be the Outlier is one of the best data science interview books if you’re in the final stages of preparing for your data science interview.
🚨 Ideal for: data science beginners
💥 Major topics: data science fundamentals, machine learning, statistics
The Data Science Design Manual by Steven Skiena isn’t specifically written for data science interview preparation. Rather, it’s a manual that has elements of interview prep.
So while we don’t think it should be the only data science interview book you look into, we think you should definitely check it out.
Treated as a textbook and reference, you’ll focus on the fundamentals of data science so you can collect, analyze and interpret data.
Instead of learning about data-analysis tools or programming languages, you’ll focus on higher-level design principles.
In addition, you’ll learn how data science crosses paths with machine learning, computer science and statistics.
🔥 Who is Steven Skiena?
Steven Skiena is the author behind the acclaimed book The Algorithm Design Manual.
The Data Science Design Manual is another banger that doesn’t skimp on the action-packed, punch of information we crave. 🥊
There are real-world stories throughout the book. You’ll also find plenty of problems to work on with detailed solutions and explanations.
There’s also an online portion that contains slides and video lectures.
🚨 Ideal for: Data scientists familiar with R and Python
💥 Major topics: applying statistics, random sampling, regression
💡 Fun fact: there are over 6,700 crab species in existence.
In our experience, statistics are a must when preparing for the data science interview.
And what better way than to tackle over 50 essential statistics concepts?
In Practical Statistics for Data Scientists, you’ll learn how to apply statistical methods to data science using Python and R programming.
- explore the benefits of random sampling to reduce bias
- discover how to use regression to estimate outcomes 📉
- look at classification techniques that can predict categories
Practical Statistics for Data Scientists is one of the best data science interview books to brush up on your statistics skills.
🚨 Ideal for: all levels
💥 Major topics: getting hired, project lifecycle, becoming a manager
If you want one of the best data science interview books for all abilities, then look no further.
Build a Career in Data Science by Emily Robinson and Jaqueline Nolis takes more of a soft skills approach to data science.
Instead of teaching you recipes and programming languages, you’ll explore things like:
- how to land a job in data science
- the lifecycle of a data science project
- how to become a manager
And much more.
What you’ll do in this book:
- Discover data science & data science companies
- Explore how to acquire data science skills
- Learn how to build a portfolio
- Get advice for finding a data science job
This includes searching for the right job and creating resumes and cover letters.
Importantly, it also covers what to expect at your data science interview.
After that, Build a Career in Data Science covers what to expect the first few months on the job.
Looking for a data science interview course? Check out The Data Science Interview Handbook on Educative.io.
Finally, you’ll discover ways to grow in your role as a data scientist. From what to do when you experience failure, to finding your perfect data science community, we loved the insights in this chapter.
Whether you’re a newbie or experienced data scientists, we think Build a Career in Data Science is one of the best data science interview books on the market right now.
🚨 Ideal for: experienced Python developers
💥 Major topics: machine learning tools, algorithms, extracting insights
Data Science Projects with Python by Stephen Klosterman is a useful tool for aspiring data scientists who need to brush up on their project-making skills in Python.
- The Bias-Variance Trade-off
- Decision Trees and Random Forests
- Gradient Boosting, XGBoost, and SHAP (SHapley Additive exPlanations) Values
- Logistic Regression and Feature Exploration
And by working on projects, you’ll be more prepared when it’s time for your data science interview. 🔥
In this revised second edition, you’ll:
- set up your data coding environment
- learn about pandas, Matplotlib, and XGBoost
- use scikit-learn to prepare data and work it into machine learning algorithms
- fine-tune your algorithms
- extract insights from unstructured data
Want to practice some data science problems? Check out Practice Coding Interview Questions in Python on DataCamp.
At the end of Data Science Projects with Python, you’ll ideally be able to use machine learning algorithms for data analysis.
You should be familiar with Python programming and have an interest in statistics before reading this book.
🚨 Ideal for: all levels
💥 Major topics: interviews with data scientists, strategies, career suggestions
In our experience, The Data Science Handbook is one of the best data science interview books for all levels of data scientists. 📊
This title is unlike our books on this list. It does not touch on the technicals of data science.
Rather, you’ll read 25 engaging interviews with some of the world’s top data scientists from companies like:
The Data Science Handbook is one of the best data science interview books if you’re looking for strategies and suggestions to kick off your data science career.
These data scientists share their perspectives on their careers, data science and life in general.
🚨 Ideal for: aspiring data scientists
💥 Major topics: statistics, Python, SQL
Crack Your Next Data Science Interview by The Data Monk is one of the best data science interview books if you love to practice interview questions.
That’s because there are over 300 questions that cover:
- R programming
And much more.
You’ll also learn what questions to expect when dealing with a telephone interview with a recruiter.
🚨 Ideal for: data scientists needing machine learning interview prep
💥 Major topics: supervised and unsupervised learning, classification and regression
More and more, data science and machine learning go hand-in-hand.
And there’s a chance you’ll come across some machine learning questions at your data science interview.
We think Cracking the Machine Learning Interview is one of the best data science interview books if you’re expecting machine learning questions at your upcoming interview.
Cracking the Machine Learning Interview by Nitin Suri contains 225 machine learning interview problems along with detailed solutions. They cover major machine learning topics such as:
- supervised and unsupervised learning
- classification and regression
- decision trees
- feature engineering
- model evaluation
And much, much more.
In addition, you’ll learn about tips and tricks to approaching real-world system design problems.
It can be tough finding data science interview books that actually list machine learning questions, so we were thrilled to find this book.
Data Science Interview Books: Recap
If you need to pass a data science interview, you’ll need to prepare. Get a leg up with one (or more!) of these top titles. From machine learning to Python, from R to Matplotlib…These books contain ample information to help you advance your data science career.
Our top two recommendations for best data science interview books:
💥 Best Overall
Ace the Data Science Interview
So whether you’re looking for best overall, value, or need to brush up on specifics, we think there are data science interview books for almost everyone.
People looking for the best data science interview books are also reading:
- Top 11 Python Books for Data Science This Year
- 9 Best Data Science Courses for Beginners
- Data Science for Non-Programmers
- Best Data Science Interview Course [Educative vs DataCamp]
- 4 Best Data Science Courses This Year