In my professional experience this is a little misguided. A pure PhD statistician isn't going to be able to hack it working on fast-paced production software environments and building end-to-end pipeline/software/ML systems. I mean, no doubt a PhD statistician could learn and be good at it, but the average statistician isn't geared up for this type of work.
On the other hand, your standard tech data scientist may find themselves out of their element if needing to design a very rigorous randomized trial for testing a new drug, and making careful inference (I mean I'm sure plenty could, but I'm not going to trust a 25 year old with two years work experience to do that).
On the other hand, your standard tech data scientist may find themselves out of their element if needing to design a very rigorous randomized trial for testing a new drug, and making careful inference (I mean I'm sure plenty could, but I'm not going to trust a 25 year old with two years work experience to do that).