Travis Gerke

By a large margin, this is the current best reference on modern data science careers and tips for navigating it. If you do not think reading about a career field will be an engrossing activity, let this book change your mind! Not only was this was the most helpful text I read in the past year, I also could not put it down. The flow of writing is excellent for a reference resource: well-delineated informational sections are interspersed with interviews and real-world examples that demonstrate the features of the data science field at hand. As a data science hiring manager who was also transitioning roles as a job-seeker this year, Build a Career in Data Science proved the all-purpose information tool I didn't know I needed. I am certain that the knowledge I gained from the book recently gave me a cutting edge in identifying appropriate roles (for myself and others) and formulating effective two-way discussions about ideal job duties. Something the authors do particularly well is cut through the confusing web of terms associated with data science roles (e.g. machine learning engineer, data engineer, decision scientist, data analyst, etc.) to settle on a few clear-cut career paths. The book will help you understand how your current skills and future goals align with each path; this refined focus will help you shine in interviews or role alignment/promotion discussions. Whether you're seeking a job or promotion, building a data science team, or generally interested in how others in the industry succeed in the field of data science, you will love this book!