[bdjsiqoocwk]

I didn't go to university for CS. Instead I did physics. Because of that, learning/remind myself of this stuff was relatively easy, and so I did it.

And let me tell you, it didn't actually made me a better data scientist/model builder, for the same reason that learning how to implement some tree traversal didnt make me a better programmer.

[quibono]

I think I'd argue with both points actually. Though it also depends on the nature of work that you do. I imagine good intuition with linear algebra is crucial for novel work. If you're implementing a model off an arxiv paper maybe not so much.

[fifilura]

Also remember that you (GP) already acquired that intuition in your youth. Most things you learn look trivial in retrospect. It may be that you already had some use of that.

And if you had not learned those things you may have started worrying what this magic thing you don't know so much about is. That can also hinder performance.

(Latd edit since I wanted to add). Another reason it is good to know stuff is to be able to dispel co-workers trying to bullshit. They are everywhere and I don't think they are trying to be mean, it is mostly insecurity. But particularly in this field I think people will start throwing buzzwords around to confuse and lead you away from what is simple and important.

But GPs comment is fine as a thought provoker.