I think at best this is fizzbuzz for DS, which is not inherently wrong. It's nice to know a software developer can write a loop and a data scientist can use a JN, so for weeding out people who have no practical experience with a given tool set, it could make sense.

The question then is how do you algorithmically (or even just consistently) distinguish a great data scientist from one who can accurately model answers to a question that was badly thought out?

Plus as pointed out before, the length of a take home could reduce applications from the most qualified candidates.

Wonder if this should be even shorter and more quiz/fun like so it intrigues rather than annoying more senior applicants, and still wondering the best way to identify the data scientists who ask better questions.