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Job Description:
Job Description:
This job is responsible for conducting quantitative analytics and complex modeling projects for specific business units or risk types. Key responsibilities include leading the development of new models, analytic processes, or system approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations may include the ability to influence strategic direction, as well as develop tactical plans.
Responsibilities:
Leads the development of AML models to support business requirements and the enterprise's risk appetite collaborating with the Technology, Global Financial Crimes, and Model Risk Management teams
Leads the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritization
Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation
Maintains and provides oversight of model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite
Leads and provides 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
Works closely with model stakeholders and senior management with regard to communication of submission and validation outcomes
Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches
Skills:
Critical Thinking
Quantitative Development
Risk Analytics
Risk Modeling
Technical Documentation
Adaptability
Collaboration
Problem Solving
Risk Management
Test Engineering
Data Modeling
Data and Trend Analysis
Process Performance Measurement
Research
Written Communications
Global Risk Analytics (GRA) and Enterprise Independent Testing (EIT) are sub-lines of business within Global Risk Management (GRM). Collectively, they are responsible for developing a consistent and coherent set of models, analytical tools, and tests for effective risk and capital measurement, management and reporting across Bank of America. GRA and EIT partner with the Lines of Business and Enterprise functions to ensure the capabilities it builds address both internal and regulatory requirements, and are responsive to the changing nature of portfolios, economic conditions, and emerging risks. In executing its activities, GRA and EIT drive innovation, process improvement and automation.
As a part of Global Risk Analytics, Global Financial Crimes Modeling and Analytics is responsible for enterprise-wide financial crime model development and implementation, ongoing performance monitoring and optimization, data usage, and research and development utilizing advanced analytical tools and systems. The Global Financial Crimes Modeling and Analytics team is made up of nine sub-teams:
7) Research and Development is responsible for future thinking concepts, innovation coordination, tools and technique assessment, artificial intelligence oversight, and vendor assessment oversight.
Overview of Role:
Responsible for independently conducting quantitative analytics and modeling projects.
Responsible for developing new models, analytic processes or systems approaches.
Creates documentation for all activities and works with Technology staff in design of any system to run models developed.
Supports the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritization
Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation
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
Works closely with model stakeholders and senior management with regard to communication of submission and validation outcomes
Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches
Qualifications:
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
Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences
Effectively creates a compelling story using data; Able to make recommendations and articulate conclusions supported by data
Effectively presents findings, data, and conclusions to influence senior leaders
Ability to work in a highly controlled and audited environment
Effective at prioritization, and time and project management
Strong Programming skills e.g. Python, SAS, SQL, or other languages
Strong analytical and problem-solving skills
Required Education and Work Experience:
Master’s degree in 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
5+ years of leadership and/or management experience
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