Top 100 Books for Data Scientists

If you want to become the wisest, most versatile data scientist you can be, then you'll love this page.

Look, we agree that the best way to learn data science is through practice. We've always believed that. (Because nothing beats real-world projects that bring all the moving pieces together.)

But good books can definitely supplement your skills. They help you become a well-rounded data scientist by expanding your mind. Below, we've listed our top 100 books for data scientists. As you’ll notice, we don’t recommend many technical books, except a few in the 'Expertise' section. That's by design!

Instead, think of a good book as a conversation with a mentor... A mentor you can bring onto the bus... A mentor who's available any time... A mentor who has condensed their life's lessons and experiences into a few hundred pages... Pretty cool, huh?

Table of Contents

Perspective Books for Data Scientists
Technology Books for Data Scientists
Business Books for Data Scientists
Career Skills Books for Data Scientists
Expertise Books for Data Scientists

Perspective

First, we start with books that can broaden your perspective. Many of these relate to data science or machine learning, but not all do. But they all can challenge the way you think about the intersection of data, machines, and humans.

Life 3.0 by Max Tegmark

An MIT professor's presentation of AI's role in the future.

Moneyball by Michael Lewis

How data and statistics changed baseball forever.

The Signal and the Noise by Nate Silver

How predictions work (and fail) in the real world.

Tools of Titans by Tim Ferriss

Wisdom from a diversity of successful people.

Outliers by Malcolm Gladwell

The story behind successful "outliers" and masters.

How to Be a Poker Player: The Philosophy of Poker

Probability, psychology, and simplifying heuristics.

Fooled by Randomness

How we perceive luck and randomness.

The Complete Sherlock Holmes

Sleuthing and the science of deduction.

The Age of Cryptocurrency

Data and the mega-trend of digitization (esp. blockchain) go hand-in-hand.

The Truth Machine: The Blockchain and the Future of Everything

The ultimate extreme in "clean data."

Quantitative Value

Metrics and feature engineering in the real world.

Thinking in Bets

Guide to decision-making from a former World Series of Poker champ.

Predictably Irrational

The behavioral psychology explanations behind the data.

Thinking, Fast and Slow

The tug-o-war between logical and illogical thinking.

Lean Analytics: Use Data to Build a Better Startup Faster

Measure -> Analyze -> Grow -> Repeat.

Creativity, Inc

Lessons for creativity from Pixar.

Human + Machine: Reimagining Work in the Age of AI

A "leader's guide" to harnessing AI in business processes.

The Smartest Guys in the Room

The story behind the infamous Enron dataset.

Dark Pools by Scott Patterson

The rise of machine traders in the stock market.

The Player of Games

Fictional series on AI that both Musk and Zuckerberg cite as inspiration.


Technology

Next, we have our favorite books on technology. Some tell the stories behind today's tech giants. Some break down key skills for building addictive products. And some offer surveys of the tech landscape and predictions for where it's heading.

Zero to One

The art and science of innovation.

Superintelligence by Nick Bostrom

Philosophical discussion of AI.

Elon Musk by Ashlee Vance

The "real-world Tony Stark."

Hooked: How to Build Habit Forming Products

Why Facebook and Candy Crush are so addictive.

How Google Works by Eric Schmidt

Insiders' look at the world's biggest Internet company.

The Everything Store by Brad Stone

The story behind e-commerce's ML giant.

Alibaba: The House that Jack Ma Built

The story behind China's e-commerce giant.

Soonish

10 emerging technologies that'll improve and/or ruin everything.

The Innovator's Dilemma by Clay Christensen

The most cited treatise on disruptive technologies.

Smartcuts: How Hackers, Innovations, and Icons Accelerate Success

How to use "lateral thinking" to get results faster.

Sprint: How to Solve Big Problems and Test New Ideas in Just Five Days

Shortening the time from idea to prototype.

The Lean Product Playbook

Using "MVP's" and rapid iteration to arrive at winning products.

The Upstarts by Brad Stone

Uber, Airbnb, and the new sharing economy.

Behind the Cloud

Scaling a SaaS business (the story of Salesforce.com).

The Second Machine Age

Overview of the tech landscape and where it's heading.

Irresistable: The Rise of Addictive Technology

A study on addiction for good and evil.

Crossing the Chasm

How to sell high-tech products to mainstream customers.

Scrum: a Breathtakingly Brief and Agile Introduction

No B.S. intro to agile development.

Bold by Peter Diamandis

How to take advantage of "exponential" technologies.

China's Disruptors by Edward Tse

The "FANG" companies of China.


Business

Data science is never done in a vacuum... and for-profit businesses are the biggest employers of data scientists. Every big business generates or uses data. So every data scientist should understand business... from strategy to marketing to financial markets.

Hedge Fund Market Wizards

In-depth interviews with 15 master hedge fund managers.

Narrative and Numbers by Aswath Damodaran

The marriage of storytelling and financial analysis.

The Lean Startup

Validating business ideas cheaply by testing and iterating.

Traction by Gabriel Weinberg

How to acquire customers consistently.

Personal MBA by John Kaufman

Spark notes of business fundamentals.

The Ten-Day MBA

10 MBA topics condensed for those who don't want an MBA.

Running Lean

KPI's for new businesses and products.

The Intelligent Investor by Benjamin Graham

Investors' perspective of businesses.

Narconomics: How to Run a Drug Cartel

Insiders' look into the biggest underground business.

The Art of War

Classic (and a bit cliché) for a good reason.

Blue Ocean Strategy

Why competition is not always a virtue.

The Effective Executive by Peter Drucker

Getting the right things done.

Grinding It Out by Ray Croc

Systems thinking at the highest level.

A More Beautiful Question

Asking better questions to spark better insights.

Rework by Jason Fried

Challenging commonly-held business assumptions.

The Essays of Warren Buffett: Lessons for Corporate America

Collection of Warren Buffett's famous letters to shareholders.

Poor Charlie's Almanac

Lessons and mental models from Warren Buffett's partner.

 

Adaptive Markets by Andrew Lo

Multi-disciplinary thesis about financial markets.

What to Do When Machines Do Everything

Primer on AI's near-future business uses.

Playing to Win: How Strategy Really Works

Strategic thinking at large corporations.


Career Skills

This section is for data scientists who want to skyrocket their careers. We have books on negotiation, project management, productivity, and more. But please go in with an open mind because there's some unconventional advice in here.

How to Win Friends and Influence People

Simple tips for improving people skills.

The ONE Thing by Gary Keller

How to prioritize for the highest impact.

Deep Work by Cal Newport

How to get sh*t done by blocking out distractions.

Principles by Ray Dalio

Life and work principles from the founder of Bridgewater.

Influence, The Psychology of Persuasion

The 6 universal "weapons of influence."

Essentialism: The Disciplined Pursuit of Less

Achieve more by doing less.

So Good They Can't Ignore You by Cal Newport

True passion is discovered only after developing real skills.

What I Wish I Knew When I Was 20

Life lessons from Stanford tech professor.

The 4 Disciplines of Execution

How to get sh*t done using a system of accountability.

Emotional Intelligence 2.0

Step-by-step program for improving EQ.

How to Fail at Almost Everything And Still Win Big

The power of systems and managing energy levels.

This Book Will Teach You How to Write Better

Simple tips for improving written communication.

The 80/20 Principle by Richard Koch

Making calculated, practical tradeoffs.

Project Management for the Unofficial Project Manager

Project Management 101 tips for any employee.

Never Eat Alone

How to build meaningful professional relationships.

Extreme Ownership: How U.S. Navy SEALs Lead and Win

How to lead, inspire, and overcome obstacles.

Getting Past No

Negotiation framework taught at Harvard Law School.

Never Split The Difference

Persuasion tactics from a former FBI hostage negotiator.

Start With Why

How to inspire your team to achieve superb results.

Reply All... And Other Ways to Tank Your Career

Hilarious guide to workplace etiquette.


Expertise

We saved the data science specific books for last. In this section, we have our favorite reference textbooks as well as some "lighter" reading. These books alone will not make you an expert... but they can complement your practice and expand your knowledge base.

How to Lie with Statistics

"There are lies, damned lies, and statistics."

Naked Statistics

Entertaining and simple primer on statistical concepts.

Statistics Done Wrong

How to avoid common statistical blunders.

Applied Predictive Modeling by Max Kuhn

Extremely practical (our favorite textbook).

Elements of Statistical Learning

Classic. But highly mathematical and not for everyone.

Introduction to Statistical Learning

Much gentler introduction to statistical ML.

Data Science from Scratch: First Principles with Python

How to code basic algorithms from scratch.

The Big Data Driven Business

Practical ways big data can help businesses.

Data Science for Business by Provost

Data analysis skills taught in an MBA course from NYU.

Data Smart: Using Data Science to Transform Information into Insight

Simple ways to start doing data science with just a spreadsheet.

Good Charts

Guide to clean, persuasive data visualizations by HBR.

Practical Statistics for Data Scientists: 50 Essential Concepts

Gentle primer on statistical methods.

Thing Explainer: Complicated Stuff in Simple Words

Can you explain machine learning concepts like this?

Spurious Correlations

Correlation does not equal causation.

Advances in Financial Machine Learning

Modern ML techniques for investors.

Deep Learning by Ian Goodfellow

Survey of deep learning by 3 prominent experts.

Make Your Own Neural Network by Michael Taylor

Intro to neural networks for visual learners.

Python Tricks: A Buffet of Awesome Python Features

Collection of Python snippets, shortcuts, and best practices.

What is a p-value anyway?

34 statistical concepts explained through stories.

Share This List