Bank of America's Global Risk Analytics (GRA) and Enterprise Independent Testing (EIT) are responsible for developing consistent models, analytical tools, and tests for effective risk and capital measurement, management, and reporting. The Global Financial Crimes Modeling and Analytics team specifically focuses on enterprise-wide financial crime model development, implementation, monitoring, and optimization using advanced analytical tools to address internal and regulatory requirements, and respond to changing portfolios, economic conditions, and emerging risks.
Requirements
- Strong Programming skills e.g. R, Python, SAS, SQL, R or other languages
- Experience with complex data architecture, including modeling and data science tools and libraries, data warehouses, and machine learning
- Knowledge of predictive modeling, statistical sampling, optimization, machine learning and artificial intelligence techniques
- Ability to extract, analyze, and merge data from disparate systems, and perform deep analysis
- Experience designing, developing, and applying scalable Machine Learning and Artificial Intelligence solutions
- Experience with LaTeX
- Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches
Responsibilities
- Responsible for leading the development of Case Generation AML model development.
- Support AML Modeling with Ad-hoc Analytics, Distribution Analysis, Sensitivity Analysis
- Support GFC with additional data analytics for drafting Business Requirement Document
- Lead analytical support for various AML interim compensating control initiatives
- Conduct and support below-the-threshold sampling
- Responsible for independently conducting quantitative analytics and modeling projects.
- Responsible for developing new models, analytic processes or systems approaches.
Other
- Master’s degree in quantitative discipline (e.g. Mathematics, Economics, Engineering, Finance, Physics) or related field or equivalent work experience
- 3+ years (2+ years with a PhD) of experience in model development, statistical work, data analytics or quantitative research
- Ability to work in a large, complex organization, and influence various stakeholders and partners
- Self-starter; Initiates work independently, before being asked
- Strong team player able to seamlessly transition between contributing individually and collaborating on team projects; Understands that individual actions may require input from manager or peers; Knows when to include others
