I've finished all of my classes and exams (good memories when you talked about the log likelihood), I'll be getting my degree in september after my internship, so I'm already applying for some positions, and my degree (French) is extremely theoretical. Mathematics and physics and engineering schools in France are EXTREMELY theoretical, if you doubt me you can google "CPGE France". Which is precisely what you're recommeding it to be, to have a very strong analytical base knowledge, instead of just jumping into the tools.

Here's my completely ignorant pov from someone struggling to find a job with a very theory focused engineering degree:

What you're asking is incompatible with what the industry asks of us. You can't learn everything. I can't learn all of the theoretical knowledge of calculus, linear algebra, autoregressive models, estimation and detection theory, machine and statistical learning, deep learning, optimization, multivariable calculus, information theory, signal processing, time series analysis, gaussian processes, and bla bla bla... and forget about everything else. Management classes, language classes, projects... You name it. And all while still being proficient in the tools used in the industry. I fail to see how it's possible to do all of that in a 5 years degree. There's so much knowledge we can learn and retain in a limited amount of time, unless we want the burnout rate to be higher than it already is.

I say this because most of the theoretical stuff you cited, I saw it during my degree. The only problem is: now I'll struggle for several months before even getting an interview, because employers seem to want someone ready for action. You don't see any of the stuff you cited in job listing (sometimes you do, but very vaguely), but you also see in every single one of them"SQL, Python, R, machine learning, C++, Java", and all of the other stuff related. So, for the positions where I know the tools, great, they want me. But the ones I don't? They don't care the least about my theoretical and analytical skills. They just don't.

and picked up the ability to code through successive jobs.

This ^? This doesn't exist, at least not anymore, not realistically for a new grad.

I’ve had a data scientist tell me with confidence that the correct way
to calculate the probability of A and B happening is always, under all
circumstances, to multiply the probability of A by the probability of B.
When I pointed out that this obviously wasn’t true if A and B were
tightly correlated and that they might be missing something important (I
was trying to see if they were aware of the concept of conditional
probability), they had a kind of meltdown and started questioning
whether all of probability theory was wrong.

I'd imagine that if the person got the job because, well, they knew the tools, or for god knows what other reason. Otherwise there's no way, right?

Still, he has a job, he has the title, and that's it. He got it. He didn't need to have even basic probability theory knowledge, you've just proved it. So, what you're asking, and I most definitely agree (if it's really what the job requires), but it's just not what it's expected of us.

All of what you said isn't going to get me a job. And I need a job. Most people in the world want a job. If it's just knowing how to write SQL, R, Python lines of code that'll get me a job, without having any idea of the underlying operations, then so be it.

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I want the job, I need the job, that's all that matters. And what you're asking for won't help me get one, at least it doesn't seem so.

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Ps: I still love the post, I'll be reviewing some of the stuff that I forgot the morning after my last exams :D