Another contender that has appeared very recently is Julia. It is a Matlab-like language designed from scratch for scientific computing by compiler and programming language experts, with a special eye to speed potential, parallelizability and syntax consistency. The language is JIT-compiled, and seems blazing fast on simple CPU-intensive benchmarks (several factors faster than Python/Matlab/R, within a small factor from Fortran and C).
It is garbage-collected; its object-oriented features are based on multiple dispatch and supports lambdas and some functional programming,
Library support is still not as large as the contenders, but I'd say it already includes everything that you can study in a first course on numerical analysis.