A little harsh, but yes in general scientists don't write great code or use the right tooling. The reason is simple : the purpose of science is not to write code
but to write papers.
That's not _at all_ to say this state of affairs is a good thing, but the practical reality is that scientists are judeged by academic papers, not code.
So, time taken learning how to code is time taken away from learning to write papers. Time taken designing code, testing it, documenting it, is time taken away from doing the research that goes into the paper. And so on.
Furthermore, most scientific code is actually scripting built on underlying frameworks. For example, plugging together a bunch of analytic tools to process some data. Or transforming data from one format to another before running it through a machine learning framework.
There _are_ scientists who write well documented, well designed framework code that is properly stored in a VCS and has release cycles, code review, etc etc. However, it is usually done in 'free time' - such as it is - and with limited resources.