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Yeah. Academia doesn't care about interesting applications, they care about novel methods.

"I made a huge difference for the business by being thoughtful about feature selection and then applying a bog-standard regression method" isn't appealing to the academic mindset.

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To be fair, people are chasing a force multiplier here. Yeah, that is a buzzy term. :( No I don't like that.

So, what I mean is that people are looking for something where they can apply one team's work and use it across many teams. The more the better. The idea is that you don't have to have many people being thoughtful producing methods, you just need many working hard applying them. If there is a better term for that, I'm game to use it.

I think an academic would be scientific in a data science role. You don't have to invent a new algorithm or tool.. just take the right approach.

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