Also, recruiters of “data scientists” with whom I’ve spoke still don’t seem to know the difference between these roles. One would thing they would get it by now.
I’m just now reading this for the first time. I love it.
Brian Godsey

I think “data scientists” are also the hardest role to fill, much the way academics who are actually good at at a domain, but also at methodology, are hard to find. Most “data science-y” training is still formulaic, although I can appreciate why — gaining necessary expertise across the multitude of techniques well enough to know the moving parts comfortably is hard enough a task, even before thinking about where things fit in. On the other hand, one should think the process should be reverse: i.e. the first step should be conceptualizing the problem, formulating the approach, and then look into the possible choice of methodologies for tackling the problem and what adaptations are needed….

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