Hey everyone. 🙂
I'm Shay (written erroneously; pronounced Shy), a data science consultant out of Israel.
I've been dedicating a lot of thought to peer review in small data science teams (like the ones I use to run, and now consult to). Sure, some of it entails reviewing code, but a lot of our work products and processes are different, and require, I believe, a dedicated peer review process.
I'd love to hear your thoughts on the topic. Is peer review a regular part of the work process in your team? Have you reviewed or been reviewed by a peer? What is your approach? What do you feel is still missing? Have you encountered any structured approaches to this process that are unique to DS/ML teams – especially small ones, where 1 project = 1 data scientist?
If you're interested in my approach so far – which we have started implementing at one of my clients', and I've actually reviewed a DS project using this procedure – you are more than welcome to take a look at this blog post, and shout at me for all of my mistakes (friends link, so no paywall): 😗
Cheers (and Coronavirus),
Source: Reddit Data Science