I work at a data science company that uses both, in a DevOps capacity. We actually have a fairly hard policy against R in production or in client deliverable code. That's mostly because of the difficulty in 'productionizing' R code, and the relative immaturity of several common R libraries. However that having been said, nearly all of our junior Data scientists from a non software engineering background do pick up R faster and feel more comfortable in it, so we mostly use it for rapid prototyping.