This is a great breakdown. Data Science can mean a lot of different things and I think the three roles you defined are spot on. At LinkedIn, what used to be called Data Science is now exclusively analyst roles. We have a separate org (hundreds of people) called Relevance which is part of the engineering org and is composed of scientists and engineers. Everyone in that org falls somewhere on the scientist to engineer spectrum with ML / Stats backgrounds and a bias towards ML engineers. Most of the people who interview would consider the relevance roles "Data Science" but the term within the company is still tightly coupled with pure analyst functions.