I think this is an insightful assessment. Not everyone in a company can be top line. But I also think there's a lot more opportunity in using statistics/ml/data science in the top line than most companies practice.
I consider myself a fairly honest Data Scientist, in the sense that I like it when I can map what I'm doing to the value it delivers. I know some other great people I've worked with who are like this as well.
This is anecdotal, but all of us have hated working with many top line people because there's some really fuzzy mapping from goal to value (since value is realized in the long term), and some of the people are champion bullshitters. I don't need to explain sales people. But marketing, corporate strategy, and even upper product management - they drove us crazy because their standard of being data driven was absolutely not consistent with how we thought about things at all. All of it was because the mapping from project to revenue was over years, not quarters. And it was all projections.
Compare this to bottom line people, where the mapping from project to cost savings is on a shorter time frame. The types of personalities this attracts is different.
Maybe the growth hacking stuff at software companies is different and you can focus on revenue growth and still connect what you are doing to that. I've never worked in that role so I don't know.
There is a large swathe of middle and upper management that gets by due to continually making sure their actual impact is never measured, and they are only a "force multiplier." not that you should do away with middle management, but there are many in middle management who could be done away with, with very marginal loss.
We all know what the problems are and where investment is needed, but management pretends that they don't know so they can have An Initiative to discover it, but not really address it (because e.g. the problem is one they caused with previous poor management).