There's likely to be some survivorship bias at play here.
Inventing new notation does not help with existing material - and that material is what makes mathematicians. People who can put up with old notation, especially if it is bad, are much more likely to become mathematicians: that gives a survivorship bias.
Besides which, you are welcome to invent your own notation, but good luck trying to get anyone to adopt it, particularly if the mathematical field involved is studied enough. Inertia is very strong, even in very abstract disciplines - aren't physicists still treating current as flowing the wrong direction?
But yeah, when working something mathematical out for the first time, picking / making up the right notation is crucial.
Having said that, I personally have never had issues with notation in mathematics nor did I have the impression others I helped had. IMO, abstraction is the main stumbling block, not notation.
But my papers need to follow the consensus, as I'm already trying to get a hard idea across to my reader who decides to spend 15 minutes to try and understand me, maybe.
So yes, then I need to introduce 15 symbols, half of them greek, and a number of operations between them using whatever line/subscript/superscript/brace is fashionable.
The biggest difference is in slides. In slides I try and can usually avoid the math notation. Because I am there talking it through, which makes notation less important and gives me an opportunity to switch to long variable names and everything a function, more akin to the software notation.
Consider einteinian notation, with implicit summation. Very terse, and very powerful when you know what you’re doing.
I’m sure CS notation is great for CS but trust me, math notation is pretty damn near optimal for math. Second only to theoretical physicists, mathematicians are probably the smartest of scientists.
Another reason is that the notation is mostly a tool for __oneself__ to think in, but is fairly bad at communicating (think about the level of expertise required to read a math paper vs reading someone’s code).
Here’s a concrete difference to support these claims. Using math notation we often write large expressions which include many meaningful subexpressions and complex operations. In code we prefer to use lots of names (variables) and simple expressions.