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Wedrux t1_ist8tqt wrote

I worked for several years now as Data scientist and now in a technical lead role and have done some Interviews.

It is so unimported if you can use pandas in one line or whatever. What matters if you understand how your model is used later, how about scaling the approach and genaralisation?

I would always take a New employee who thought about these aspects over one who blindly trains a model but 10 minutes faster.

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yourmamaman t1_istbg9n wrote

I also hire DSs and I do the same as you.

My assumption is that these types of interviews were designed by consultancy companies for companies that don't have experienced DSs of their own.

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Dihedralman t1_iswmh38 wrote

The kind of consultansies that recommend lines of code as a productivity measurement.

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yourmamaman t1_iswqhqx wrote

This is where the statement "Something is better than nothing" fails.

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marr75 t1_isxnz3w wrote

I think they're designed by very traditional engineering managers. The coding test trend gained popularity thanks to Jeff Atwood because he used it as an early screen for people applying for lucrative jobs they didn't actually know how to do (which is useful!). Managers were using it as a higher and higher floor for skills and we got the leetcode style (a fresh bootcamper might pass fizzbuzz but they're unlikely to have months to grind leetcode). We've also seen an explosion in roles who code but are more responsible for the wisdom and value of their creations (the spec and visual design aren't enough or even relevant for a model, a Lagrangian relaxation, a recommendation engine, etc).

Real conversation I had with another executive, "Hey, we've got that coding screener for engineers, can we whip up something similar for [name a role]?" You start combining these different forces - a desire for selectivity, a desire to lower hiring cost, more complex technology roles that have to chart some of their own spec, and just human laziness - and you get what OP described.

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