It's complicated. The Army Corps of Engineers has had a civilian mandate to support flood control prevention since 1917 [1]. Beyond that, they are also involved in large public works projects such as the building of roads and bridges, and Superfund clean-up sites. On top of this, they regularly receive large pork barrel grants from Congress that can siphon money into a senator's state or a congressperson's district. They do have a large contracting arm and are actually pretty well-regarded for their comprehensive procurement and management process for these large public works projects.
So it's scale, politics, and history/momentum at this point.
Ilan Schnell is not "some guy". He's the original primary author of the Anaconda distribution. One of the main reasons that so many data scientists use Python.
NumPy is a library that provides typed multidimensional arrays and functions that run atop them. It does provide a built-in LAPACK/BLAS or can link externally to LAPACK/BLAS, but that's a side effect of providing typed arrays and is nowhere near the central purpose of the library.
Also, NumPy is implemented completely in C and Python, and makes extensive use of CPython extension hooks and knowledge of the CPython reference counting implementation, which is part of the reason why it is so hard to port to other implementations of Python.
So it's scale, politics, and history/momentum at this point.
[1] https://en.wikipedia.org/wiki/U.S._Army_Corps_of_Engineers_c...