Conduct quantitative modeling and analytics of financial crimes
Perform a broad range of quantitative works, including model development and ad hoc analytics to address financial crime compliance needs
Research, compile and evaluate large sets of data to assess quality and determine suitability for model building
Develop/maintain internal models and test/configure vendor solutions to ensure conceptually sound design, proper implementation, and acceptable model performance
Document model development process and outcomes properly and support model validation and review
Employ innovative techniques to drive continuous improvements in model effectiveness and efficiency, e.g. reducing false positives
Proactively develop and build technical skills and business knowledge; effectively 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, technology, and data analysis best practices
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 which may include production, commission, and/or discretionary incentives.

Senior Data Scientist, Financial Crimes

Key skills