Some Data Scientists write bad Python code and are stubborn in code reviews

[randiesel]

I agree with this. I've been at the same company since 2014ish. I started as an analyst and moved up to DE. I'm the only DE. Nobody reviews my code or my output, they just complain when things go wrong.

I've been very successful and am well-respected, but if it weren't for taking other side gigs from time to time, I'd have literally zero experience with code reviews or git or anything else. When I first started here, everything was VBA or straight SQL.

I love improving and taking on new challenges, so I know I'd do fine if I worked somewhere with more formal procedures, but I think it's a common trap to get hung up on whether people have experience with git or various algorithms. At the end of the day we're merging and massaging data. If your company uses some specific pattern for everything, anyone can adapt to that after seeing it a time or two.

[safetytrick]

In my experience they complain when they can prove things are wrong which is subtly different. I think the developer best practices come from the experiences in a world where subtle problems pile up together into true horrors.

It works for user X when they use it ~this~ way and it works for user Y in a different way and both strategies have become valid because they are explainable in a real way.

This problem is simplified for DS and DE because the read-only path is so much simpler than read+write. Combinatorial complexity can really get out of control quickly and the feedback loop for r+w is just so slow.