I'm in ML and I would also like an answer to this question.

I've seen a lot of Python people sprinkle imports all over the place in their code. I suspect this is a bad habit learned from too much time working in notebooks where you often have an "oh right, I need XXX library now" and just import it as you need it.

The aggressive aliasing I do get since in DS/ML work it's very common to have the same function do slightly different things depending on the library (standard deviation between numpy and pandas is a good example)

But I personally like all of my imports at the top so I know what this code I'm about to read is going to be doing. I do seem to be in the minority in this (and would be glad to be correct if I'm make some major error).