Bank of America is looking to solve problems related to financial crime detection and prevention by developing and maintaining models for Anti-Money Laundering (AML) and other financial crime activities, particularly for non-US markets. This involves analyzing large datasets, identifying suspicious activities, and ensuring compliance with regulatory guidelines.
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 data analytics tools (e.g., Alteryx, Tableau)
- Experience with LaTeX
Responsibilities
- Performs end-to-end market risk stress testing including scenario design, scenario implementation, results consolidation, internal and external reporting, and analyzes stress scenario results to better understand key drivers
- Supports model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite
- Supports the methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of development/validation projects and identify areas of potential risk
- Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches
- Responsible for model inventory management, model development and enhancement, model tuning and optimization, model risk management, and model analysis and incident management
- Responsible for development and maintenance of Non-US AML Feeder models to address the regional regulatory guidelines while meeting the bank’s AML Risk Coverage.
- Automates suspicious activity monitoring while optimizing the effectiveness and the efficiencies of our models for the detection of potential threats.
Other
- Effectively creates a compelling story using data; Able to make recommendations and articulate conclusions supported by data
- Demonstrated ability to drive action and sustain momentum to achieve results
- Experience with engineering complex, multifaceted processes that span across teams; Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflow
- Sees the broader picture and can identify new methods for doing things
- Master’s degree in related field or 2+ years equivalent work experience
