99.99% of finance is freshman level math if at that. Then 99.99% of the remaining 0.01% is somewhat more complicated but still not frontier level.
There are very-very few cases where you need truly advanced math in finance. The problems that need solving are generally vastly more pedestrian.
You need to deal with terrible data quality, terrible formats, noise in every aspect of your work, disruptions, lack of standards, inability to generate new data (and repeat experiments), conflicting and often opaque incentives, technical problems ranging from shitty APIs to having to squeeze nanoseconds out of your network stack, etc.
These are all difficult problems, but they are crucially not frontier math problems (by and large).
99.99% of finance is freshman level math if at that. Then 99.99% of the remaining 0.01% is somewhat more complicated but still not frontier level.
There are very-very few cases where you need truly advanced math in finance. The problems that need solving are generally vastly more pedestrian.
You need to deal with terrible data quality, terrible formats, noise in every aspect of your work, disruptions, lack of standards, inability to generate new data (and repeat experiments), conflicting and often opaque incentives, technical problems ranging from shitty APIs to having to squeeze nanoseconds out of your network stack, etc.
These are all difficult problems, but they are crucially not frontier math problems (by and large).
Or Cryptanalysis.
" The National Security Agency is the largest employer of mathematicians in the U.S. "
https://www.scientificamerican.com/article/mathematicians-an...
Or signals intelligence.