Are Google data scientist jobs basically applied statisticians? Their blog (http://www.unofficialgoogledatascience.com) almost solely about statistics and inference. Do they do applied ML, analytics, metrics, etc.?
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When I interviewed for a data scientist job, it was all applied stats. No ML, no analytics. It was a rude realization (I’m an ML expert, not a super awesome statistician (although I know some stuff)).
I don't get how this is possible? How can you be an expert in ML and not be extremely solid in statistics.
Yeah, I know. I’m solid in stats, I promise. But my PhD is in computer science. I can program. DS at google has no programming component in the interview. It was a lot of causality questions and straight math. I’m more applied. It just wasn’t a good fit, and it wasn’t what I expected. The DS team at Google = all phds in stats. I’m an applied scientist at amazon, and it’s a much better fit. The DS role at Amazon is a lot different than the one at google too. “DS” is such unstandardized term: I think it makes programming and applied stats. Google thinks it’s straight stats and the SWEs do all the programming.