[ylmm]

I think it depends a lot on what it is that you want to do. For example, there are entire teams at companies like Facebook (Core Data Science) and Netflix that hire exclusively people with PhDs. Amazon especially is famous for hiring economists. Microsoft pours huge sums of money into Microsoft Research where the only goal is to fund research with relatively little (short-run) profit motive.

But if you're not on one of these research-oriented teams, then I think it's easy to look at PhDs on your own team and think of them as worthless when in fact they were trained for a pretty different set of things. There's the thing about judging a fish's ability to climb a tree. People seem relatively eager (see other comments) to rip into people with doctoral training for some reason.

[tinyhouse]

But there's a difference. Microsoft Research indeed hires mostly PhDs as researchers. That makes sense since they do academic research and publish papers like they are in academia. People with PhDs spent years in grad school doing exactly that.

In other places it makes less sense. And it's good not to make generalizations. If we take ML as an example, there are many excellent people without a PhD and also many PhDs that are great engineers and can write code as good as the best engineers.

[ylmm]

Ah, I think you've misunderstood entirely.

I meant the teams in those companies as opposed to the companies more broadly (e.g., Core Data Science at Facebook, not Facebook in general). I mention those companies together because they're well-known for investing a lot in research (e.g., by hiring PhDs). And in these cases, they're hiring PhDs for reasons that are totally different from the reasons for which they hire engineers (who may also have doctorates). For example, there is indeed a difference between the institution-level goals of Facebook and Microsoft Research, but that difference is less substantial between researchers at Core Data Science at Facebook and researchers on the Computational Social Science team at Microsoft Research.

I'm making the point that there is a difference in the value of a PhD depending on where in the company you work. For the research-oriented teams, the value of a PhD lies in the fact that you've ostensibly been trained to contribute to what we know, rather than just applying it.

Going along with your ML example, the difference would be like comparing Athey, Tibshirani, and Wager's work on generalizing random forests against building a random forest using scikit-learn. I'm not saying that someone without a PhD can't write the paper that they did, but it's for sure not at all just a matter of who's better at writing code.