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"Mastery in that they know the business capability from end-to-end". That's the point. These generalists are not really data scientists. Often it's some account
by potatofarmer45 8y ago
"Mastery in that they know the business capability from end-to-end". That's the point. These generalists are not really data scientists. Often it's some account manager/salesperson/ops worker rebranding themselves to get ahead. A real data scientist who understands the business side is rare and really good, but most "generalists" are just bad. So bad in fact they exacerbate every single problem the author thinks they solve: Having bs people called data scientists devalues and annoys the real data scientists; and they often create confusing buzzword driving plans and white elephants for show rather than insight that will have a real impact.
I worked in a media agency once where an account manager who could barely do a simple calculation in Excel rebranded himself as a "lover of data". All he did was play office politics. We nicknamed him unicorn. It was a nice way to describe a creature with a thin rod sticking out of its head.
He was such a leech in that he was full of incorrectly used buzzwords, overpromising, and overselling (he had a habit of present non-significant analysis as facts). The very idea of statistical confidence was a mystery to him.
Because he played the politics game well, he did reasonably well and ran a few projects. Every single one of those turned out to be a giant white elephant to the clients.
- itronitron 8y agoWhat you're describing is not a generalist. Generalists can actually do things and it sounds like your colleague was just pretending. I have worked with one or two people similar to what you describe, they can pose a real risk to their employer if they are not managed appropriately.
- yannis7 8y agowe've all dealt with such people and I hear you on all the concerns raised. But as pointed out, what you describe has nothing to do with the "generalist vs. specialist" debate