Table of Contents

Introduction

The rise in popularity within data science over the past few years has led to a major boom in interview prep-books and courses as publishers fight to establish the newest go-to guide for one of the most ambiguous interviews ever.

Today, we at Interview Query are going to look at some of the top data science interview books to help you decide how to review before the next big interview. Of course while we always thing you should use Interview Query before anything else, we wanted to go over some of the useful paperback material that we've read in the past few years.

And no, Cracking the Data Science Interview does not exist yet

Cracking the Data Science Interview

Anyone even remotely involved in computer science or adjacent fields knows of the "Cracking the Coding Interview"– and with Gayle Laakmann McDowell’s continual success in her following book, Cracking the PM Interview, it was only a matter of time before the production company planned for the release of an accompanying Data Science Interview guide.

Unfortunately, with the official publication date still undetermined, candidates are left scrambling to find other reliable resources to successfully prepare for their interviews.

The namesake "Cracking the Data Science Interview" on Amazon is one such guide, released by an author and publishing company unaffiliated with McDowell. Early reviews are inconclusive as to the quality and helpfulness of the text, so we’ll be focusing on other guides for this article.

Heard in Data Science Interviews (2018)

Book cover image from GoodReads

"Heard in Data Science Interviews" boasts an astonishing selection of 650+ data science interview questions across all the major data science topics, including algorithms, statistics, computer science, modelling, etc.

Written by Kal Mishra, a data scientist with almost ten years of industry experience, this guide is intended to cut out ‘fluff’ portions often found in interviews, focusing mainly on “genuine AI questions”.

Pros:

  • This book covers essentially almost every topic that can be sure to come up in your data science interview– making this a powerful study tool for content review.
  • The flash-card style text is great for skimming and quick review! If you’re looking for an easy reference brush up on your knowledge right before an interview, this may be the book for you.

Cons:

  • Unfortunately, the synopsis proves too good to be true: early readers complain of distracting grammar errors, as well as an appendix with numerous mistakes across the answer key.
  • Some questions are said to be overly vague and frustrating, which is only compounded by unclear explanations given in the answer key.

Overall:

While this book may be helpful for new interviewees looking for a comprehensive guide, persistent complaints of the errors in Heard in Data Science Interviews’ answer key make us hesitant to whole-heartedly recommend it.

At almost $50 (one of the highest price points on our list!), there are sure to be better options out there without the glaring flaws present in this text.

120 Data Science Interview Questions (2014)

Content cover image from Data Science Questions

Written by data scientists for data scientists, this collection of questions covers the typical data science topics: programming, stats, probability, etc.

Unique across all the other books on our list, "120 Data Science Interview Questions" also lists a Communication section, designed to tackle those infamous interview questions asking you to describe certain concepts in non-technical terms.

Pros:

  • Reviewers have described this text as the unofficial data science edition of “Cracking the Coding” guide.
  • Questions are given in a case-study like format, forcing you to think and investigate thoroughly while developing a solution. Unlike the pure knowledge tests (“Explain XXX”) found in other guides, the prompts here will more closely mimic what an actual interview will consist of.
  • At $19, this is one of the most affordable study tools found on our list.

Cons:

  • Since this guide’s publication in 2014, data science has advanced rapidly with industry standards. As such, some of the sections (like Programming or Product Metrics) may contain outdated questions/answers.
  • Purchasing this guide only provides access to roughly 25 crowd-sourced answers out of 120 questions. Given the format of the questions, it may be difficult to research answers for the other prompts on your own.

Overall:

Out of all of the guides reviewed in this article, 120 Data Science Interview Questions offers the most fleshed out, interview-esque questions typically found in data science interviews.

For those looking to practice talking through solutions, this may be the perfect guide for you! For data scientists trying to first establish a firm content foundation, you may need to look elsewhere for a more comprehensive reference with a complete answer key.

The Data Science Handbook (2015)

Book cover image from The Data Science Hand Book

From the same authors of 120 Data Science Interview Questions comes "The Data Science Handbook", a collection of 25 interviews from well-established data scientists about their perspectives in the field.

Unlike the other selections in this article, "The Data Science Handbook" doesn’t cover interviewing techniques or topics, but rather discusses the career trajectories of successful data scientists navigating their way through the industry.

Pros:

  • This handbook is FREE (small donations accepted) in ebook format and $25 on Amazon, making this an affordable resource for learning more about data science careers.
  • Reading more about the perspectives of other data scientists may help you brainstorm for those tough culture-fit and ‘Why data science?’ type of questions.

Cons:

  • For last minute studying before an important interview, this handbook won’t be very helpful for content review or practicing questions.
  • Published in 2015, this guide may be a little outdated if you’re looking for fresh perspectives on the data science field.

Overall:

If you’re looking for help preparing for an incoming interview, this book may not be the best main resource for you. While it provides valuable insights into the careers of many famous data scientists, your time would probably be better spent with other guides that focus directly on interview structures and style.

For those looking for general information about data science or who are interested in how different data scientists had their breakthroughs, read away!

Data Science Interviews Exposed (2015)

Book cover image from Amazon

Written by a collective of data scientists, "Data Science Interviews Exposed" was one of the first data science interview guide books available on the market. In addition to the standard technical interview topics present in many similar texts, this book reviews job search procedures and standard screening interview processes.

Pros:

  • Readers looking to transition from other fields gave overwhelmingly positive reviews for the introductory chapters that discuss the data science field and job qualifications.
  • The technical problem sets are slightly more difficult and fleshed out than typical guidebooks, offering good practice for more experienced data scientists.

Cons:

  • Errors abound– unfortunately, early reviewers complain of heavy grammatical errors and awkward sentence structures. While the answer key is definitely more comprehensive than other texts we’ve reviewed thus far, mistakes in some solutions are another negative factor readers have taken note of.
  • For applicants who just want practice for technical interviews, the five sections before the problem sets may seem like unnecessary ‘fluff’ pieces.

Overall:

At a price point of $50, this book definitely isn’t the most cost-effective or efficient way to review for your data science interview. Newer data scientists may appreciate the insights into job searches and soft skills, but this information can also be found in collated online blog posts and resources from current data scientists.

From a technical standpoint, this guidebook may not also be the best resource depending on your experience level and the quantity of questions.

Which book to buy for your next interview?

The chosen book from Unsplash

After investigating each of these guides, it has become evident that there’s no one perfect book that can effectively cover all the possible topics for a successful data science interview. Ultimately, in 2020, a guide book may not be the best way to learn and prepare.

Innately in data science exists the necessity of practicing SQL, Python, or R in an interpreter, as well as a general need for actively updating content foundations with the field rapidly changing over time with new technological processes. This simply isn’t possible with a book, which is why we ultimately recommend seeking out other online resources for your needs.

If you’re interested in preparing for your next interview, be sure to check out Interview Query and join the community of thousands of data scientists practicing for their next interview.