I think this is correct. So a DS does a bunch of stuff. - Some of the stuff becomes diffused and common. Anyone can do it. - Some of the stuff becomes data en

I think this is correct. So a DS does a bunch of stuff. - Some of the stuff becomes diffused and common. Anyone can do it. - Some of the stuff becomes data engineering. - Some of the stuff becomes fitting a model -- anyone can do it. - Some of the stuff ends up subsumed in a cloud providers offering and mostly automated. - Some of the stuff becomes a SaaS (e.g. A/B testing). Death by factorisation. Specialisation is another sort of death, where X doesn't need a "Data scientist" any more, they need a "X data scientist". A bit like how "scientific computing" is just programming, except you wouldn't hire "just" programmers to do it -- you hire programmers who specialise in scientific computing.