Conduct quantitative modeling and analytics of financial crimes
Research, compile and evaluate large sets of data to assess quality
Develop/maintain internal models and test/configure vendor solutions
Document model development process and outcomes
Employ innovative techniques to drive continuous improvements in model effectiveness and efficiency
Collaborate with compliance, technology, and risk partners

Master’s or Ph.D. degree in statistics, mathematics, economics, computer science, data sciences, predictive modeling, or other quantitative disciplines
At least 3 years of relevant experience, preferred in AML/BSA, OFAC, or fraud modeling/analytics; 4 years with bachelor's degree
Solid expertise with both traditional and Machine Learning (ML)/Artificial Intelligence (AI) modeling practice and solutions
Hands-on work experience with statistical coding in SAS and/or Python
Knowledge of and ability to leverage traditional databases, cloud-based computing, and distribution computing
Knowledge of financial crime regulatory requirements
Excellent verbal, written and visual communication skills; ability to translate technical observations to a non-technical audience
Candidates must be located in or willing to relocate to Cleveland, OH or Buffalo, NY.

Eligibility for incentive compensation
Flexible options in circumstances where roles can be performed effectively in a mobile environment

Senior Data Scientist, Financial Crimes

Key skills