Checklist for assessing a data science team

I'm starting a new job managing a data science team. The team was traditionally a SAS-heavy team, now transitioning to a more modern python based approach. There's a separate data engineering teams so this team is mainly model-building.

Does anyone with experience managing in this environment have a first-30-days checklist for things they'd look for as you start with a new team?

Here's examples of what I mean:

-- does the team use version control well?
-- is code style …

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