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Wanted to highlight Prudential Financial’s hiring practices. They rescinded my offer once I attempted to negotiate the salary. The official reason given was that I didn’t “sound excited enough”.
They then admittedly gave the offer to someone who was less qualified. There were other red flags throughout the job offer process that the HR team should overall be ashamed of.
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At Deloitte this week
Anyone have belt recommendations?
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Thought this was interesting. Across 160 teams of researchers, just about all failed to make good life outcome predictions on things like GPA, evictions, layoffs, and others. Data followed 4.5k families across 15 years, with 13k features (varied over time). Haven't looked at it directly yet, but will be turning the docs and data inside out... In the meantime, authors claim this as showing the limits of ML. Oh, and it's published in PNAS, so you know there's some big publication energy there.
https://www.pnas.org/content/117/15/8398
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Depends on what kind of FAANG data scientist. Are we talking FB style product analytics DS or research / stats oriented DS? The former is much more common and doesn't require hardcore technical skills besides some SQL tricks. The business skills help with the product sense questions which are basically cases.
The more research / stats focused DS is a whole other ball game and requires serious studying outside case work because in consulting nobody cares about theory.
Also, if someone can put few pointers on Apple vs MBB data Scientist, same profile, almost similar salary structure. How does things May look 5 years down the line?
I had two rounds for FAANG this year, for MLE. They test you thoroughly on Computer Science fundamentals, and Systems Design with a touch of ML. There is also a data science aspect to it where they might probe you on basic statistics.