Upvoting. I found myself nodding in agreement for the most part but I think you're being a bit uptight about labels.

People appropriate what label they will. Some of them will "fake it until they make it" and some will just use it as a flashy label. I think the problem, in some cases, is also how non-practitioners perceive people who do predictive or machine learning work.

I'm fortunate enough to work in the business unit of an organization where I can actually work on and formulate subject area hypothesis and design projects to test out that hypothesis with real data. My counterparts in IT shops are more like ML-using data engineers. Do I begrudge them for the title because they don't have subject matter expertise? Not really.

For someone who works with data and probabilities, it's not terribly helpful to view the world in black and white terms -- ie data scientist vs not data scientist. How many project managers in your company do you see that don't manage anything or anyone?

Disclaimer, I leaned on R programming skills to "fake it til I make it." I had been on the fence about using the title for a long time