I use R extensively, even more than Python, but it is not a robust language when your problem moves from exploration to anything resembling production. The memory management appears to be the problem. Hugely inefficient and slow even with 3.x. I get crashes frequently, even under Linux and I run production on R. Moreover, Numpy's two orders-of-magnitude speed increase opens up a new class of problem that R just can't handle, especially in the streaming data space. Pandas has made a big improvement in taking Python towards R, though it would be great if it were multidimensional. Where R has Python beat hands down is in its "vectors everywhere" functional philosophy. List comprehensions just don't match the power, and vector indexing is uneven even in Pandas.

I have less experience with Matlab for cost, and lock in reasons. I need to have the option to distribute my code easily.