It's easy to find ways to a feature launch a success, especially if basic metrics are neutral to positive. Who cares if the differences are statistically significant? We shipped fast! We paved the way for future innovation! And it is fun to use and looks great!
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this is a great thread
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Glad you liked it! It's partly intended as an expression of my existential angst, but I figure thinking out loud can help find the folks who are in similar situations
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@threadreaderapp unroll pls -
Hola, the unroll you asked for:
@imightbemary: What is the difference between an engineering manager and a data science manager? It's a question I find… https://threadreaderapp.com/thread/1279836969044852738.html … See you soon.
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So what you describe as Type A DS sounds like my role as staff scientist bioinformatician in academic research group. Except I also develop / extend tools to handle new analyses
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My boss' job is to be a sounding board for ideas / methods, find collaborators, and keep me on task, especially when something is dragging on and on and on. Now academic collabs are different than customers (most of the time)
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I used to have a type B team and I was trying to build a type A team - struggled a lot a few years ago. I wish I had the kind of clarity that you have I might have fared better. Great thread!
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Great thread, thank you
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Super interesting to read from academic perspective. Would you say a type A DS manager is conceptually similar to a research PI/lab head in science?
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This is spot on
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