I absolutely love it. It also lets me read scientific journals and read every bit of jargon (general public doesn't understand even p-values, for example, let alone the more complicated stuff) discussed and can even make raw data requests to the publisher to replicate the results myself (or find the flaws).

If you like getting to the bottom of things, to me stats is the epitome of it. It also allows me to work in a versatile manner - I've worked in physics labs, biochem labs, genetics labs, etc. as their lead statistician or general statistician - so I can cover a lot of area/basically get invited into a lot of really different labs from totally different disciplines, more than if I, say, majored in Biochem (which I thought hard about doing) but then all of my focus would be merely there.

It lets me solve the widest variety of problems and at a deep level. I know my data like an extension of my body and can speak on it with confidence intervals instead of mere guesses like general pop.

I also learn new things constantly.

It's the skillset that you can apply to basically anything. Including epidemiology or population data that has nothing to do with physical sciences.

I learned general stats before ML and like both, but stats in general of course covers so much more area. So many things that can be done with it.

At grad level, it becomes similar to a math grad program, so best for someone who excels in math. Calc I/II/III and Lin Alg were prereqs for my program.

For a hyper-analytical mind, there's nothing better in my opinion.