Bingo. The typical data scientist has a masters or PhD in a non-CS quantitative field, and has had exactly zero CS or software eng classes. It’s a shame, because once you get over some of the idiosyncrasies, R is a really powerful and flexible functional language.
I was a programmer, and moved over to biology recently. I was very "wtf is R" when I started, but slowly its strengths are coming through. I found the combination of the REPL plus the IDE, and the language syntax, somehow give me the ability to play around a lot more than I expected. Unlike others, I find tidyverse (especially ggplot2 and dplyr, which reminds me a lot of pandas) to be quite intuitive.
