I would think about which of these you see yourself doing more.. * statistical methods (more math) * big, in-production model fitting (more python) * quick,

I would think about which of these you see yourself doing more.. * statistical methods (more math) * big, in-production model fitting (more python) * quick, scrappy data analyses for internal use (more R) For example, I would feel weird writing a robust web server in R, but it's straightforward in python. On the other hand R's shiny lets you put up quick, interactive web dashboards (that I wouldn't trust in exposing to users).