Ability to code using R or Python for customer segmentation and data analytics.
Ability to solve problems through mathematical and deductive reasoning.
Familiarity implementing, testing or evaluating performance of financial crime and compliance systems.
Proven track record of strong quantitative testing and statistical analysis techniques as it pertains to BSA/AML models, including name similarity matching, classification accuracy testing, unsupervised/supervised machine learning, neural networks, fuzzy logic matching, decision trees, etc.
Familiarity of current compliance rules and regulations of the FRB, SEC, OCC, FATF, FinCEN, OFAC, and familiarity with USA PATRIOT Act, BSA/AML and OFAC screening regulations.
Prior experience designing compliance program tuning and configuration methodologies, including what-if detection scenario analytics, excess over threshold, and sampling above/below-the-line (ATL/BTL) testing.
Working knowledge of one or more of the following programming platforms: SAS, Matlab, R, Python, SQL, VBA, etc.
Familiarity with vendor models like Actimize SAM, SAS, SearchSpace, Mantas, OTUS, or SIRON.