Project Euler # 22: Names scores
Here's your problem:

return sum(letters_map[char]*(names.index(name)+1) for name in names for char in name)
                              ^^^^^^^^^^^^^^^^^^^


So as we walk down names, we calculate the value of the current name... and then start over and search for it from scratch to determine the index. That extra lookup turns our algorithm from \$O(n)\$ to \$O(n^2)\$!! And string search is expensive - for the 1000th name, we have to first check 999 other strings that are definitely going to be wrong. We don't need to search for name in names to find the index. Not only that, but then we re-search the index for every char in name! (Maybe Python is smart enough to cache this, maybe not). So really this is more like \$O(n^3)\$...

We can just keep track of the index as we go. That's what enumerate() is for:

return sum(letters_map[char] * idx
           for idx, name in enumerate(names, start=1)
           for char in name)


That one change takes your runtime over 10 iterations from 13.31s to 0.07s. Behold the power of not redoing a bunch of work. 



Everything else is basically fine. Creating letters_map could be abridged to just:

letters_map = {letter: idx
               for idx, letter in enumerate(string.ascii_uppercase, start=1)}


That doesn't affect performance, just makes it a little easier to see what letters_map actually is. It turns out that dictionary lookup is fater than doing the name lookup on ord() within the loop is, so this is pretty speedy. 

It's also typical to do file operations with a context manager. That is:

with open(file_name) as f:
    return sorted(re.findall(r'"(.*?)"', f.read()))


That is marginally slower, but more Pythonic in my opinion.