When I started my first data-science role, the role description of my company sounded a bit like "software engineer who happens to know stats and ml". The description was fairly specific on the fact that data scientists would build and deploy models and services. Nowadays it seems not to fall under the software engineering umbrella. And I do think the change started with the deep learning craze. It distorted a lot in the field. Nowadays I see so many overfitting and complicated models that cannot be operated in production. But they sure make impressive slides and reports.