Not much an argument at all, if you ask me. There's definitely a benefit to only having to learn a single language (rather than R and C++), but the library/package ecosystem in R is hard to beat; unless you're doing truly bespoke computational work, the number of mature statistical libraries/packages in R is unmatched. Rcpp's syntactic sugar means most slow R bottlenecks can be written in C++ almost verboten, but without the interpreted performance penalty. One of R's best and under-emphasized features is its straightforward foreign-function interface: it's easy to creating bindings to C/C++/Fortran routines (and Rust support is coming along as well).

I've been impressed with Julia, but it's hard to beat 25 years of package development.