Python has always had a good selection of scientific/mathematical libraries (numpy, scipy).

In addition, notebook apps like Jupyter fit well with the experimental nature of scientific code. I have a colleague who was attempting to do some stuff in Ruby (to fit with our application stack) who would leave IRB sessions open for weeks at a time. He's recently switched to Zepplin for notebook stuff, and it has been a huge productivity boost for him.