[emmanuel_1234]

This is precisely why I dread hiring academic-only profile. Note: I am myself from academia, but I was lucky enough to specialized in CS-related field (NLP). When I wanted to leave academia, Data Science was not a thing where I live and I had to start again at a junior dev position (i.e.: it was that, starving or staying in academia).

Now, I work with a lot of people way smarter than I am, who are mostly useless because they can hardly prototype their stuff in Python or run an SQL query. And they'd expect to only work on the best, cleaned and formatted dataset and only do high-end maths on those. Reality hits hard, we're losing money paying them and they're wasting their time not doing what they like. Add to that the frustration / jealousy that this creates.

In that regard, I like that famous definition for Data Scientist: "A programmer that know more about statistics than most programmers, or a statistician that knows more about programming than most statisticians".

And don't get me started on the general repulsion for understanding the basics of how a business runs from academia. Data Science is all about application.

[jensv]

https://medium.com/incerto/surgeons-should-notlook-like-surg...

[chillee]

I've always heard the definition of data scientist as "Somebody who knows less about programming that programmers and less about statistics than statisticians"