I think its more intuitive for statistical applications where Python is grossly under-represented. This includes things like the design and analysis of experiments but also lots of domain specific statistics and algorithms such as in bioinformatics, chemistry, and so on.

Typically those applications are not the sort of line-of-business enhancements ML in Python is more tuned to. I.e. recommender systems, NN models, and so on.