Over my career I’ve thought a lot about “where should a data scientist sit in an org?” 👇 5 lessons from what I’ve learned after working in 6 very different companies.
- DS under an MBA: maybe okay, probably bound for failure.
- DS under the PM: def bound for failure.
- DS under the DS: good for the junior in the short term.
- DS under Eng: good.
- DS under a people manager, but works closely integrated team with a DS-experiences tech lead: best.
Interdisciplinary teams do the best work. It maximizes labor efficiency to have engineers, PMs, and DS’s working on the same problem but doing different things.
When you federate DS, they don’t care as much about what they’re working on. The incentives are off.
When a DS works for a PM the PM will make wild assumptions about what they should do. PMs oversimplify problems and DS find that unsatisfying.
DS reporting to DS means you throw stuff over the fence and the Eng do the real work. And the Eng don’t capture all the nuance the DS would like to implement.
DS reporting to business types is unfulfilling because DS love technical stuff.
best scenario? Have a DS work in a pod with experienced tech leads. DS reports (HR purposes) to someone outside of the team who can give them guidance but is incapable of micromanaging them.
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Bryan lives somewhere at the intersection of faith, fatherhood, and futurism and writes about tech, books, Christianity, gratitude, and whatever’s on his mind. If you liked reading, perhaps you’ll also like subscribing: