Industrial engineering. I did lots of statistical related math, a lot of "collect observational data to create baseline". Change something. " Collect observational data on new scenario." Do the statistics /math to creat a model of how labour is spent (or profist made, or utilities generated, per unit of X).

Heavier, more complext math -- I did quite a bit of queing theory -- such as line ups for airline checkin, or at a retail store, or at a cafeteria.

Simulation software was fun to figure out, too. -- how many snow desposit lanes do we need to build to keep the snow plows a peak efficiency for offloading at the new site, for a 100 year storm even, when the population is to grow at 3% per year for the next 20 years, and we have two or three entrances?

When I did environmental engineering, carbon mass balances, models for water/lake system flow and simple mathematical models for hydrology, waste water engineering systems for reactors to treat organic waste, and my favorite, heat transfer for conservation of utilities...

I also did a lot of cost benefit analysis, sometimes using these models that could get pretty complex, almost like a mini-software program.

I don't have a maths degree, just a bachelor in engineering, and I was very very tempted to take a grad course or two in multivariable design of experiments because of the complex studies I would set up (e.g., if we gave more hours to the bakery department, how does that impact sales, despite other variations in weather and foot traffic that occurs in week B versus baseline week A?). I never did. My MBA helped a bit with the cost / benefit analysis, so your accounting background would serve you well, there.

ETA - my DH uses a lot of math in programming and in design of gas sensors. Each motor, fan, needs math to calibrate and to size it, and there is a model for how the sensors pick up on gas concentrations, by temperature, that he needs to program into the design.