I work at a quant firm and we use Python because of how painful it is to build things in C++. Our framework is built in C++ but we then expose all of it to Python using pybind11 (amazing library).

Most quants do not want to learn complex build systems that have quirky behavior on different platforms, wait for very long compile times when making small changes to the code, dense and incomprehensible error messages, and a host of painful problems that one has to consider when writing C++.

Python just works really well on almost all platforms.

The biggest downside of Python is its parallelism, which means there is a lot of hackyness around writing parallel code. In most cases we can break things down and run different tests independently of one another, but in many other cases we have to make use of awkward workarounds, use multiprocessing, and other tricks.