Some of it is simple stuff, like CPython being interpreted, so PyPy get's a huge boost by JITting.
Some of it is much harder stuff, like the way Python is designed to store objects in memory (a list is a pointer to a contiguous space of pointers to things that might be pointers...), and everything that hangs off each object (everything has a dict), and the awful GIL ([0]). Awful for performance, great for thread-safety.
Every single part of a language design has trade-offs. It depends on what you're trying to do whether or not they help you, or hinder you.
Sometimes you change how you're doing things because priorities change, and get a radical improvement, like Python's 3.6 Dict. Most of the time, you don't. One step at a time. Not being able to break backwards compatibility hinders the designer, if they realise a trade-off they've made was a mistake. So you get stuck with some features you'd rather not have.
To be sure, the internal implementation of CPython (the only one I'm familiar with) is complicated as hell. But it's a whole lot simpler than any fast JavaScript runtime I've ever used. I think that's the result of a conscious choice by the maintainers/BDFL/community in Python, not a side effect of it having less funding (assuming that's the case).