I work as a mathematician/tools engineer in casino gaming (class 2/bingo based slot machines), so I think I fit this description (math first, software second).
People that have this skillset (knowledge of Monte Carlo methods for statistical analysis/verification) are useful in this sphere.
An example problem we deal with is as follows:
We have some arbitrary histogram (list of slot game awards and probabilities), and we wish to map this to a particular game of bingo (N ball calls out of M balls in total, 5x5 bingo card). The constraint here is that when you come up with a list of bingo patterns for awards, they are ordered in the sense that when evaluating the set of bingo patterns, from top-down, the first bingo pattern that matches is awarded and the evaluation stops.
Getting the optimal fit theoretically in the general case requires exponential time, as the chain of P(this pattern given (not-that pattern and not-other pattern and not-...)) grows with an exponential number of operations in the theoretical expansion. Each time a new pattern is fit to an element of the histogram, the probabilities of all remaining possible patterns to fit changes.
There are a few ways of tackling this problem in a more optimal way: If you can solve this with good enough accuracy in linear time with a good math/cs background, you’d be useful to any company playing in this space.
People that have this skillset (knowledge of Monte Carlo methods for statistical analysis/verification) are useful in this sphere.
An example problem we deal with is as follows:
We have some arbitrary histogram (list of slot game awards and probabilities), and we wish to map this to a particular game of bingo (N ball calls out of M balls in total, 5x5 bingo card). The constraint here is that when you come up with a list of bingo patterns for awards, they are ordered in the sense that when evaluating the set of bingo patterns, from top-down, the first bingo pattern that matches is awarded and the evaluation stops.
Getting the optimal fit theoretically in the general case requires exponential time, as the chain of P(this pattern given (not-that pattern and not-other pattern and not-...)) grows with an exponential number of operations in the theoretical expansion. Each time a new pattern is fit to an element of the histogram, the probabilities of all remaining possible patterns to fit changes.
There are a few ways of tackling this problem in a more optimal way: If you can solve this with good enough accuracy in linear time with a good math/cs background, you’d be useful to any company playing in this space.