I believe the comment was in reference to the supercomputing (HPC) world where Python is indeed very popular and has great libraries for doing large-scale scientific computing. You lose quite a bit of performance on the hardware but it makes up for it in speed of programming. For small-scale scientific computing other languages tend to be used.
The best language for large-scale scientific computing is C/C++, which surprises some people. Python binds to these libraries. C/C++ has two big advantages: it can run much faster than any other language and the language is better suited for designing massively parallel codes than most others. The latter point makes sense when you realize that HPC software only runs a single process per core and explicitly, adaptively schedules execution and messaging in order to optimize throughput. It is a bit like very old school single-threaded UNIX server programming.
The best language for large-scale scientific computing is C/C++, which surprises some people. Python binds to these libraries. C/C++ has two big advantages: it can run much faster than any other language and the language is better suited for designing massively parallel codes than most others. The latter point makes sense when you realize that HPC software only runs a single process per core and explicitly, adaptively schedules execution and messaging in order to optimize throughput. It is a bit like very old school single-threaded UNIX server programming.