Sooo, not too long after some clever person figures out how to automate 80% of the grunt work of building an analytics pipeline and their colleagues dumb down the 20% left so that the people inhabiting the C-suite can work it on their iPads...?
I know at least three startups working that space, right now. And there are probably another 300 on the way.
Of course there aren't. The best way is to know exactly the causal process generating the data, thus enabling you to predict your variable-of-interest perfectly from the limited data.
This isn't currently possible, of course, but there's one best way to interpret data, not an infinity.
For your tortured analogy to bear any fruit you have to assume that we're just waiting to find a dead simple set of equations that explains all human endeavor, and after that finite memory and computation power won't be an issue because, hey, cause and effect.
As far as I'm aware doing probability and statistics correctly is all about framing the problem correctly. You can, for example, accidentally assume that two events are independent when they're really dependent. Is it even possible to detect that kind of mis-framing automatically?
I'd also point out that most of the jobs on your list are specific roles in specific industries - data science as a concept will be more resilient because it's an evolving set of skills (as is programming/software engineering) that span basically the whole economy. The day people no longer have a reason to build systems using computers is the day these jobs will go away.