Machine Learning Interviews

Chapter 1. Machine Learning Roles and the Interview Process

In the first part of this chapter, I’ll walk through the structure of this book. Then, I’ll discuss the various job titles and roles that use ML skills in industry.¹ I’ll also clarify the responsibilities of various job titles, such as data scientist, machine learning engineer, and so on, as this is a common point of confusion for job seekers. These will be illustrated with an ML skills matrix and ML lifecycle that will be referenced throughout the book.

The second part of this chapter walks through the interview process, from beginning to end. I’ve mentored candidates who appreciated this overview since online resources often focus on specific pieces of the interview but not how they all connect together and result in an offer. Especially for new graduates² and readers coming from different industries, this chapter helps get everyone on the same page as well as clarifies the process.

The interconnecting pieces of interviews are complex, with many types of combinations depending on the ML role you’re aiming for. This overview will help set the stage, so you’ll know what to focus your time on. For example, some online resources focus on knowledge specific to “product data scientists,” but will title the course or article “data scientist interview tips” without differentiating. For a newcomer, it’s hard to tell if that is relevant to your own career interests. After this chapter, you’ll be able to tell what skills are required ...