Best Data Science Interview Books

Book rating updated 10.05.2024

Ranking the best data science interview books of all time. Prepare for interview excellence!

  1. Ace the Data Science Interview

    4.5
    991 ratings

    Comprehensive guide—the whole array of data scientist interview questions from FAANG companies, frameworks for quantitative analysis, fundamentals of machine learning, probability, coding exercises, and behavioral questions. Packed with practice problems and detailed solutions, this must-read book gives the candidate a reservoir of core concepts and skills to become a strong data science professional.

  2. Becoming a Data Head

    4.6
    325 ratings

    A pragmatic guide on how to build the right mindset and skills toward success in today's data-driven business. The book will delve into key concepts, tools, and techniques employed in data analysis and visualization to enable the readers at any level of technical literacy. Using real-world examples and case studies, it will help in driving home the power of making data-driven decisions.

  3. Machine Learning System Design Interview

    4.5
    113 ratings

    Focuses on the system design aspect of machine learning interviews. Major topics include data ingestion, processing pipelines, model deployment, and scaling ML systems. It develops a structured approach for readers in system design and enlightens them on the real-world challenges ML practitioners face.

  4. Cracking The Machine Learning Interview

    4.1
    123 ratings

    Nitin Suri demystifies the technical machine-learning interview process used by major tech companies. He explains the evaluation rubrics and further details different questions dealing with coding in Python. It is a really good comprehensive guide that can help demonstrate your knowledge in ML from end to end.

  5. Build a Career in Data Science

    4.6
    100 ratings

    This book is an excellent resource that will lead professionals from all backgrounds to transition into a data science role. It explains what skills and tools one needs to learn, including statistical learning concepts, stats, and their practical application in data science projects. The latest edition also covers which projects should be included in the portfolio, how to write a resume, and how to go through the entire interview process - all in this comprehensive roadmap of breaking into this hot field.

  6. The Data Science Handbook

    4.5
    63 ratings

    This comprehensive reference is designed to help you land your dream data science job by providing all the tools you need to prepare for data science interviews. It covers a wide range of topics, including data munging, exploratory analysis, product analytics, and concepts related to machine learning, offering a high-level overview as well as practical advice. It's a very hands-on data science book that equips you with many real-life Python code examples and exercises—certainly at the level of depth an average candidate can expect in a technical interview.

  7. Be the Outlier

    4.1
    60 ratings

    This best-selling book, often referred to as the bible for data science interview preparation, sees Shrilata Murthy leverage over 20 years of experience in the field to empower readers with career guidance and technical preparedness. She prepares them for critical areas in data science, offering a unique mix of perspective on mathematics, programming, analysis, and communication by reviewing real-world examples to ace interviews.

  8. Cracking the Data Science Interview

    3.9
    63 ratings

    Maverick Lin's comprehensive playbook to acing the data science interviews at the topmost companies. It breaks down significant skills, such as coding, statistics, machine learning, and product sense, into examples, practice questions, and unique ways of problem-solving so that the candidate can depict not only depth in technical knowledge but also their thought process.

  9. Heard In Data Science Interviews

    3.2
    53 ratings

    The only uniqueness available in this interview prep book is the preparation of interviews for data analyst and data science roles, with a comprehensive list of compiled questions asked by the top tech companies. Each chapter spans most of the data science concepts in breadth, from statistics to machine learning to databases and beyond, which you'll find beneficial in helping the candidate understand the expectation of depth of understanding and prepare for it.

  10. Data Science Interviews Exposed

    3.0
    35 ratings

    This book is a valuable resource for aspiring data scientists looking to ace their interviews. It provides an exclusive look behind the scenes into the interview process with firsthand stories and case studies from data science experts, making it a great supplement to other interview preparation materials. The authors recommend strategies for tackling different types of questions, including those related to analytics, as well as tips for anxiety management and presentation communication skills, all of which can help one stand out in data science interviews.

  11. Inside the Machine Learning Interview

    4.8
    21 ratings

    This book provides valuable insights on how to sail through data science and machine learning interviews, even in top tech companies. It covers core ML algorithms, model validation techniques, and, lately, system design and applied math concepts, giving readers a comprehensive idea of what to expect in these interviews. The book includes frequently asked questions and real-life examples, which prepare readers for any situation they might encounter during the interview process. Although not a traditional textbook, it offers practice drills that help readers thoroughly prepare and perform at their best.

FAQ

  • What are the best data science interview books ever written?

    These are the top 7 best books for data science interview of all time and for this year (2024) sorted by rating:

    1. "Cracking the Data Science Interview" by Maverick Lin and Benjamin Bengfort
    2. "Data Science Interviews Exposed" by Yanping Huang, Irina Truong, Caroline Wan, and Rebecca Yen
    3. "The Data Science Handbook" by Carl Shan, William Chen, Henry Wang, and Max Song
    4. "Ace the Data Science Interview" by Nick Singh and Kevin Huo
    5. "120 Data Science Interview Questions" by Kojin Oshiba
    6. "Heard in Data Science Interviews" by Kal Mishra and Deepak Agarwal
    7. "The Data Science Interview" by Saurabh Agarwal.
  • What are the most popular authors of data science interview books?

    Here are authors of good books about data science interview:

    • Guido van Rossum ("Python for Data Science Handbook")
    • Jake VanderPlas ("Python Data Science Handbook")
    • Wes McKinney ("Python for Data Analysis")
    • Joel Grus ("Data Science from Scratch")
    • Andriy Burkov ("The Hundred-Page Machine Learning Book")
    • Andreas C. Müller and Sarah Guido ("Introduction to Machine Learning with Python").