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Somewhat of a side-question, but how would one go about about finding jobs where knowing Monte Carlo methods is a primary requirement? It seems most companies w

Somewhat of a side-question, but how would one go about about finding jobs where knowing Monte Carlo methods is a primary requirement? It seems most companies want a software developer that knows a bit of this, rather than a statistician/mathematician that knows a bit of software development.

guerby 6y ago
Quant teams in financial derivatives do lots of Monte Carlo and probably incorporating state of the art Math knowledge in their code.
mlthoughts2018 6y ago
In general what you’re looking for just doesn’t exist. In niche cases it might, and your best bet would be government / military / academic research labs. Those jobs pay comparatively worse but usually have much better work/life balance & job security and enable you to focus on specializations. In industry, you just won’t find this. Statistics is a small domain specialist component of a much larger software ecosystem. You don’t require advanced statistics, you just might want to try it or derive a special benefit from it, and none of that will be worth it unless it efficiently connects to the regular software development life cycle, architecture patterns, testing, and maintenance processes that the larger system requires. Someone who can do “a little software development” would be a liability in that scenario, no matter what their other domain specializations are. That’s why you’ll find most data scientists and ML engineers professionally are highly skilled at software engineering. They approach statistical modeling tasks from the point of view of standard software development life cycle tasks where the components just happen to involve statistical models or techniques.
- MacsHeadroom 6y ago
  Quants are statisticians who know a bit of software development. They're always in high demand and get paid more than SWEs on average. https://www.linkedin.com/jobs/quantitative-analyst-jobs https://www.linkedin.com/jobs/quantitative-analyst-jobs
  - mlthoughts2018 6y ago
    I worked as a quant for several years at the start of my career. Being a quant is 95% software architecture and engineering and 5% stats / SQL / spreadsheets and analytics.
arsenide 6y ago
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.

guerby 6y ago

Quant teams in financial derivatives do lots of Monte Carlo and probably incorporating state of the art Math knowledge in their code.

mlthoughts2018 6y ago

In general what you’re looking for just doesn’t exist. In niche cases it might, and your best bet would be government / military / academic research labs. Those jobs pay comparatively worse but usually have much better work/life balance & job security and enable you to focus on specializations. In industry, you just won’t find this. Statistics is a small domain specialist component of a much larger software ecosystem. You don’t require advanced statistics, you just might want to try it or derive a special benefit from it, and none of that will be worth it unless it efficiently connects to the regular software development life cycle, architecture patterns, testing, and maintenance processes that the larger system requires. Someone who can do “a little software development” would be a liability in that scenario, no matter what their other domain specializations are. That’s why you’ll find most data scientists and ML engineers professionally are highly skilled at software engineering. They approach statistical modeling tasks from the point of view of standard software development life cycle tasks where the components just happen to involve statistical models or techniques.

MacsHeadroom 6y ago
Quants are statisticians who know a bit of software development. They're always in high demand and get paid more than SWEs on average. https://www.linkedin.com/jobs/quantitative-analyst-jobs https://www.linkedin.com/jobs/quantitative-analyst-jobs
- mlthoughts2018 6y ago
  I worked as a quant for several years at the start of my career. Being a quant is 95% software architecture and engineering and 5% stats / SQL / spreadsheets and analytics.

arsenide 6y ago

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.