I'm not sure I believe you that Haskell is faster than Python. In general, most of your python operations will be raw matrix operations handled by blas/lapack/etc.

While Python's functional programming constructs leave a lot to be desired, they are usually good enough for numerical work. Instead of using reduce(...) to sum an array and having it compile down properly, you can just use arr.sum(), which is implemented in C by numpy anyway.

I love Haskell (and want it to beat Python), but at this point, Python is the clear winner for numerical work. Libraries matter more than language in this case (as matlab demonstrates).