In my experience, this is true:
> "data scientists" are expected to be the equivalent of full-stack engineers (or maybe more accurately: one-man CTO shops)—to understand data architecture, understand business architecture, ensure data quality, build data into product, build dashboards, derive insights, posit hypotheses, set strategy, and drive business value.
But this is not:
> Thus many "data scientists" are juiced-up report-builders who can't analyze their way out of a paper bag.
Rather, the data scientists are trained in only two of the requirements you mentioned: derive insights, posit hypotheses. The rest is all self-study and on-the-job experience. This means that we are putting unrealistic expectations on data scientist and/or their training is insufficient, not that data scientists are somehow morons.