Table of Contents

**Got a data science interview coming up?**

Not to worry.

Today we’re looking at 8 data science interview books to help you prepare for – and ace – your data science interview.

*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 🔥****Build a Career in Data Science****💸 Best Value 💸****Be the Outlier: How to Ace Data Science Interviews**

**Data Science Interview Books**

**1. The Data Science Design Manual**

🚨 **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.

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.

**🔥 Geena’s Hot Take**

Steven Skiena is well-known for his 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. 🥊

**2. Practical Statistics for Data Scientists**

🚨 **Ideal for:** R and Python developers

💥 **Major topics:** applying statistics, random sampling, regression

💡 *Fun fact: there are over 6,700 crab species in existence.*

Statistics are a *must* when preparing for the data science interview. And what better way than to tackle over 50 essential concepts?

In **Practical Statistics for Data Scientists** by Peter Bruce, Andrew Bruce and Peter Gedek, you’ll learn how to apply statistical methods to data science using Python and R programming.

You’ll also explore the benefits of random sampling to reduce bias. Then you’ll discover how to use regression to estimate outcomes. 📉

Finally, you’ll 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.

**3. Build a Career in Data Science**

🚨 **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.

First you’ll learn about data science and data science companies. From there you’ll explore how to acquire your data science skills and build a portfolio.

Next you’ll learn how to find that data science job. This includes searching for the right job, resumes and cover letters, and even what to expect at the data science interview.

After that, **Build a Career in Data Science** covers what to expect the first few months on the job.

Finally, you’ll discover ways to grow in your role as a data scientist. So you’ll touch on what to do when you experience failure. And you’ll learn how to find a data science community.

**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 today.**

*Looking for a data science interview course? Check out The Data Science Interview Handbook on Educative.io.*

**4. Data Science Projects with Python**

🚨 **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.

**And by working on projects, you’ll be more prepared when it’s time for your data science interview.** 🔥

First you’ll learn how to set up your data coding environment.

Then you’ll gain insight and experience with industry standard data analysis and machine learning tools such as pandas and Matplotlib. After that, you’ll use scikit-learn to prepare data and work it into machine learning algorithms.

You’ll also explore how to fine-tune your algorithms to deliver accurate data predictions.

At the end of **Data Science Projects with Python**, you should be able to use machine learning algorithms for data analysis. You should also be able to extract insights from unstructured data.

**You should be familiar with Python programming, algebra and statistics before reading this book.**

**5. The Data Science Handbook**

🚨 **Ideal for:** all levels

💥 **Major topics:** interviews with data scientists, strategies, career suggestions

**The Data Science Handbook by Carl Shan, William Chen, et al. is one of the best data science interview books for all levels of data scientists.** 📊

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:

And more.

These data scientists share their perspectives on their careers, data science and life in general.

**The Data Science Handbook is one of the best data science interview books because it contains strategies and suggestions to start your data science career.**

*Want to practice some data science problems? Check out Practice Coding Interview Questions in Python on DataCamp.*

**6. Be the Outlier: How to Ace Data Science Interviews**

🚨 **Ideal for:** interviewing data scientists

💥 **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. So here is where you’ll find questions on:

- modeling
- machine learning
- probability
- statistics
- case

And beyond.

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. It can be almost 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.**

**7. Crack Your Next Data Science Interview with 300+ Questions**

🚨 **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:

- statistics
- Python
- R programming
- SQL
- Excel

And much more.

You’ll also learn what questions to expect when dealing with a telephone interview with a recruiter.

More than 80% of these questions were asked at companies like Amazon, Accenture and Cognizant.

**8. Cracking The Machine Learning Interview**

🚨 **Ideal for:** 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 good chance that you’ll come across some machine learning questions** at your data science interview.

**So that’s why we included this book.**

**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.

**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.**

**Data Science Interview Books: Conclusion**

**Today we looked at the best data science interview books. Two stood out:**

**Best Overall****Build a Career in Data Science**

**Best Value****Be the Outlier: How to Ace Data Science Interviews**

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.

**Up Next:**

- Top 11 Python Books for Data Science in 2021 [Learn Data Science using Python]
- 9 Best Data Science Courses for Beginners [+4 Data Science Learning Paths]
- Data Science for Non-Programmers [Educative Course Review 2021]
- Best Data Science Interview Course in 2021 [Educative vs DataCamp]
- 4 Best Data Science Courses of 2021 [Educative, DataCamp, Zero to Mastery, Codecademy]

**What are the best data science interview books?**We picked two of the best data science interview books. Overall, we think Build a Career in Data Science is the best. And for value, we chose Be the Outlier: How to Ace Data Science Interviews.

**Is Build a Career in Data Science worth it?**If you want one of the best data science interview books, 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 projects, and much more. The book is separated into four parts.

First you'll learn about data science and data science companies. From there you'll explore how to acquire your data science skills and build a portfolio. Next you'll learn how to find that data science job. This includes searching for the right job, resumes and cover letters, and even what to expect at the data science interview. After that, Build a Career in Data Science covers what to expect the first few months on the job.

Finally, you'll discover ways to grow in your role as a data scientist. So you'll touch on what to do when you experience failure. And you'll learn how to find a data science community.**Is the book Be the Outlier worth it?**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. So here is where you'll find questions on modeling, machine learning, probability, statistics, and beyond. Then you'll learn how to showcase your experience with data science. This includes projects you've worked on and behavioral interview questions. 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 for you if you're in the final stages of preparing for your data science interview.