I have not with that specific scenario. But, I think splitting them out is a great idea and it's one I would do in that instance.
For my example, I do the same for another version of SQL and it works out great. Both R and Python can run separate in their own environment with their own dedicated resources that does not hog the data warehouse. In that instance, I can directly scale up the R and Python workloads as needed without ever impacting the data warehouse and other processes that may be running.