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.
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.