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Is a Ph.D necessary for competing for those high salaries? It hasn't been for other CS jobs, and from my experience with ML and NLP - it seems wildly unnecessary. I'd pick experience over a degree every time.



Presumably the "fresh Phds" getting 300k right out of school have extremely relevant experience and are quite capable of actually putting their learning to use (I don't have data to prove this).

People who just know TF and couldn't implement it and know what it does and doesn't do well aren't the kind of people attracting 7 figures.

There's a huge amount of advanced statistics, math, and "intuition" that takes years working with data to build. Abstractions like TF (etc.etc.) make applying existing solutions to existing problems more tractable, but the real gold-rush is happening around the new/relatively-unsolved problems.


One thing I've heard - and it seems plausible - is that one skill that's desired for these positions is the ability to consume and make use of academic research. If you have a PhD you've done that, and in a sense you are a practitioner of reading research.


I've seen top Kaggle competitors get some of those jobs. But I believe those are more pratictoners than researches.


No, not at all. A master's does help significantly, but it's possible to get these jobs with any background.




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