Executive Data Science
Minimum price
Suggested price

Executive Data Science

A Guide to Training and Managing the Best Data Scientists

About the Book

In this concise book you will learn what you need to know to begin assembling and leading a data science enterprise, even if you have never worked in data science before. You’ll get a crash course in data science so that you’ll be conversant in the field and understand your role as a leader. You’ll also learn how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles. You’ll learn the structure of the data science pipeline, the goals of each stage, and how to keep your team on target throughout. Finally, you’ll learn some down-to-earth practical skills that will help you overcome the common challenges that frequently derail data science projects.

If you are interested in a printed copy of this book, you can purchase one at Lulu.

About the Authors

Brian Caffo
Brian Caffo

Brian Caffo, PhD is a professor in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. Along with Roger Peng and Jeff Leek, Dr. Caffo created the Data Science Specialization on Coursera. Dr. Caffo is leading  expert in statistics and biostatistics and is the recipient of the PECASE award, the highest honor given by the US Government for early career scientists and engineers.

Roger D. Peng
Roger D. Peng

Roger D. Peng is a Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health where his research focuses on the development of statistical methods for addressing environmental health problems. He is the author of the popular book R Programming for Data Science and 10 other books on data science and statistics. He is also the co-creator of the Johns Hopkins Data Science Specialization, the Simply Statistics blog where he writes about statistics for the public, the Not So Standard Deviations podcast with Hilary Parker, and The Effort Report podcast with Elizabeth Matsui. Roger is a Fellow of the American Statistical Association and is the recipient of the Mortimer Spiegelman Award from the American Public Health Association, which honors a statistician who has made outstanding contributions to public health. He can be found on Twitter and GitHub at @rdpeng.

Jeffrey Leek
Jeffrey Leek

Jeff is a professor of Biostatistics and Oncology at the Johns Hopkins Bloomberg School of Public Health and co-director of the Johns Hopkins Data Science Lab. His group develops statistical methods, software, data resources, and data analyses that help people make sense of massive-scale genomic and biomedical data. As the co-director of the Johns Hopkins Data Science Lab he has helped to develop massive online open programs that have enrolled more than 8 million individuals and partnered with community-based non-profits to use data science education for economic and public health development. He is a Fellow of the American Statistical Association and Mortimer Spiegelman Award recipient.

Table of Contents

  • A Crash Course in Data Science
    • 1. What is Data Science?
      • Moneyball
      • Voter Turnout
      • Engineering Solutions
    • 2. What is Statistics Good For?
    • 3. What is Machine Learning?
    • 4. What is Software Engineering for Data Science?
    • 5. Structure of a Data Science Project
    • 6. Output of a Data Science Experiment
    • 7. Defining Success: Four Secrets of a Successful Data Science Experiment
    • 8. Data Science Toolbox
    • 9. Separating Hype from Value
  • Building the Data Science Team
    • 10. The Data Team
    • 11. When Do You Need Data Science?
      • The Startup
      • The Mid-Sized Organization
      • Large Organizations
    • 12. Qualifications & Skills
      • Data Engineer
      • Data Scientist
      • Data Science Manager
    • 13. Assembling the Team
      • Where to Find the Data Team
      • Interviewing for Data Science
    • 14. Management Strategies
      • Onboarding the Data Science Team
      • Managing the Team
    • 15. Working With Other Teams
      • Embedded vs. Dedicated
      • How Does Data Science Interact with Other Groups?
      • Empowering Others to Use Data
    • 16. Common Difficulties
      • Interaction Difficulties
      • Internal Difficulties
  • Managing Data Analysis
    • 17. The Data Analysis Iteration
      • Epicycle of Analysis
    • 18. Asking the Question
      • Types of Questions
    • 19. Exploratory Data Analysis
    • 20. Modeling
      • What Are the Goals of Formal Modeling?
      • Associational Analyses
      • Prediction Analyses
    • 21. Interpretation
    • 22. Communication
  • Data Science in Real Life
    • 23. What You’ve Gotten Yourself Into
      • Data double duty
      • Multiplicity
      • Randomization versus observational studies
    • 24. The Data Pull is Clean
    • 25. The Experiment is Carefully Designed: Principles
      • Causality
      • Confounding
    • 26. The Experiment is Carefully Designed: Things to Do
      • A/B testing
      • Sampling
      • Blocking and Adjustment
    • 27. Results of the Analysis Are Clear
      • Multiple comparisons
      • Effect sizes, significance, modeling
      • Comparison with benchmark effects
      • Negative controls
    • 28. The Decision is Obvious
      • The decision is (not) obvious
      • Estimation target is relevant
    • 29. Analysis Product is Awesome
    • About the Authors
  • Notes

Authors have earned$10,257,955writing, publishing and selling on Leanpub, earning 80% royalties while saving up to 25 million pounds of CO2 and up to 46,000 trees.

Learn more about writing on Leanpub

The Leanpub 45-day 100% Happiness Guarantee

Within 45 days of purchase you can get a 100% refund on any Leanpub purchase, in two clicks.

See full terms

Free Updates. DRM Free.

If you buy a Leanpub book, you get free updates for as long as the author updates the book! Many authors use Leanpub to publish their books in-progress, while they are writing them. All readers get free updates, regardless of when they bought the book or how much they paid (including free).

Most Leanpub books are available in PDF (for computers), EPUB (for phones and tablets) and MOBI (for Kindle). The formats that a book includes are shown at the top right corner of this page.

Finally, Leanpub books don't have any DRM copy-protection nonsense, so you can easily read them on any supported device.

Learn more about Leanpub's ebook formats and where to read them

Write and Publish on Leanpub

You can use Leanpub to easily write, publish and sell in-progress and completed ebooks and online courses! Leanpub is a powerful platform for serious authors, combining a simple, elegant writing and publishing workflow with a store focused on selling in-progress ebooks. Leanpub is a magical typewriter for authors: just write in plain text, and to publish your ebook, just click a button. It really is that easy.

Learn more about writing on Leanpub