About This Book

Build a Career in Data Science was written to help you enter the field of data science and grow your career in it. It walks you through the role of a data scientist, how to get the skills you need, and the steps to getting a data science job. After you have a job, this book helps you understand how to mature in the role and eventually become a larger part of the data science community, as well as a senior data scientist. After reading this book, you should be confident about how to advance your career.

Who should read this book

This book is for people who have not yet entered the field of data science but are considering it, as well as people who are in the first few years of the role. Aspiring data scientists will learn the skills they need to become data scientists, and junior data scientists will learn how to become more senior. Many of the topics in the book, such as interviewing and negotiating an offer, are worthwhile resources to come back to throughout any data science career.

How this book is organized: a roadmap

This book is broken into four parts, arranged in the chronological order of a data science career. Part 1 of the book, Getting started with data science, covers what data science is and what skills it requires:

• Chapter 1 introduces the role of a data scientist and the different types of jobs that share that title.
• Chapter 2 presents five example companies that have data scientists and shows how the culture and type of each company affects the data science positions.
• Chapter 3 lays out the different paths a person can take to get the skills needed to be a data scientist.
• Chapter 4 describes how to create and share projects to build a data science portfolio.

Part 2 of the book, Finding your data science job, explains the entire job search process for data science positions:

• Chapter 5 walks through the search for open positions and how to find the ones worth investing in.
• Chapter 6 explains how to create a cover letter and résumé and then adjust them for each job you apply for.
• Chapter 7 provides details on the interview process and what to expect from it.
• Chapter 8 is about what to do after you receive an offer, focusing on how to negotiate it.

Part 3 of the book, Settling into data science, covers the basics of the early months of a data science job:

• Chapter 9 lays out what to expect in the first few months of a data science job and shows you how to make the most of them.
• Chapter 10 walks through the process of making analyses, which are core components of most data science roles.
• Chapter 11 focuses on putting machine learning models into production, which is necessary in more engineering-based positions.
• Chapter 12 explains how to communicate with stakeholders—a task that data scientists have to do more than most other technical roles.

Part 4 of the book, Growing in your data science role, covers topics for more seasoned data scientists who are looking to continue to advance their careers:

• Chapter 13 describes how to handle failed data science projects.
• Chapter 14 shows you how to become part of the larger data science community through activities such as speaking and contributing to open source.
• Chapter 15 is a guide to the difficult task of leaving a data science position.
• Chapter 16 ends the book with the roles data scientists can get as they move up the corporate ladder.

Finally, we have an appendix of more than 30 interview questions, example answers, and notes on what the question is trying to assess and what makes a good answer.

People who haven’t been data scientists before should start at the beginning of the book, whereas people who already are in the field may begin with a later chapter to guide them in a challenge they’re currently facing. Although the chapters are ordered to flow like a data science career, they can be read out of order according to readers’ needs.

The chapters end with interviews of data scientists in various industries who discuss how the topic of the chapter has shown up in their career. The interviewees were selected due to their contributions to the field of data science and the interesting journeys they followed as they became data scientists.

liveBook discussion forum

Purchase of Build a Career in Data Science includes free access to a private web forum run by Manning Publications where you can make comments about the book, ask technical questions, and receive help from the author and from other users. To access the forum, go to https://livebook.manning.com/#!/book/build-a-career-in-data-science/discussion. You can also learn more about Manning's forums and the rules of conduct at https://livebook.manning.com/#!/discussion.

Manning’s commitment to our readers is to provide a venue where a meaningful dialogue between individual readers and between readers and the author can take place. It is not a commitment to any specific amount of participation on the part of the author, whose contribution to the forum remains voluntary (and unpaid). We suggest you try asking the author some challenging questions lest their interest stray! The forum and the archives of previous discussions will be accessible from the publisher’s website as long as the book is in print.