After defending my master's thesis this summer I was presented an opportunity to apply machine learning in anti-money laundering(AML) and anti-terror efforts at Scotiabank. This was great for me, as I became increasingly interested in national security and researching organized crime books over the last two years of grad studies.
Even newer to machine learning applications than sports analytics, detecting money laundering has just in the last few years been introduced to using models from deep learning. Other than just focusing on machine learning applications in detecting financial crime, there is a ton of opportunity behind scaling reporting and analysis work into microservices for consumption.
Unfortunately I will be limited in what I share on my blog. Most will focus creating simple service architectures using open source technology. Any machine learning analysis in AML will be done using open source data.