Job Description:

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities, and shareholders every day. Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being a diverse and inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing, and rewarding performance, and how we make an impact in the communities we serve. Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

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:

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 driversLeads the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritizationIdentifies 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/validationMaintains and provides oversight of model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetiteLeads 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 riskWorks closely with model stakeholders and senior management with regard to communication of submission and validation outcomesPerforms statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches

Skills:

Critical ThinkingQuantitative DevelopmentRisk AnalyticsRisk ModelingTechnical DocumentationAdaptabilityCollaborationProblem SolvingRisk ManagementTest EngineeringData ModelingData and Trend AnalysisProcess Performance MeasurementResearchWritten Communications

Minimum Education Requirement: Master’s degree in related field or equivalent work experience

Line of Business Job Description:

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: Modeling and Analytics Teams are responsible for model inventory management, model development and enhancement, model tuning and optimization, model risk management, and model analysis and incident management

Overview of Role:
Responsible for leading the development of AML transaction monitoring or Customer Due Diligence (CDD) modeling independently.
 

Responsibilities include, but not limited to:

Support AML and CDD Modeling with Ad-hoc Analytics, Distribution Analysis, Sensitivity AnalysisSupport GFC with additional data analytics for drafting Business Requirement DocumentLead analytical support for various AML/CDD interim compensating control initiativesConduct and support below-the-threshold samplingResponsible 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.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 driversSupports the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritizationIdentifies 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/validationSupports model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetiteSupports 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 riskWorks closely with model stakeholders and senior management with regard to communication of submission and validation outcomesPerforms 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 partnersSelf-starter; Initiates work independently, before being askedStrong 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 othersStrong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiencesEffectively creates a compelling story using data; Able to make recommendations and articulate conclusions supported by dataEffectively presents findings, data, and conclusions to influence senior leadersAbility to work in a highly controlled and audited environmentEffective at prioritization, and time and project managementStrong Programming skills e.g. R, Python, SAS, SQL, R or other languagesStrong analytical and problem-solving skill

Desired Skills and Experience:

Experience with complex data architecture, including modeling and data science tools and libraries, data warehouses, and machine learningKnowledge of predictive modeling, statistical sampling, optimization, machine learning and artificial intelligence techniquesStrong technical writing, communication and presentation skills and ability to effectively communicate quantitative topics with non-technical audiencesEffective at prioritization/time and project managementBroad understanding of financial productsAbility to extract, analyze, and merge data from disparate systems, and perform deep analysisExperience designing, developing, and applying scalable Machine Learning and Artificial Intelligence solutionsDemonstrated ability to drive action and sustain momentum to achieve resultsDemonstrated leadership skills; Ability to exert broad influence among peersExperience with engineering complex, multifaceted processes that span across teams; Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflowSees the broader picture and is able to identify new methods for doing thingsExperience with LaTeX

Education:

Graduate degree in quantitative discipline (e.g. Mathematics, Economics, Engineering, Finance, Physics)3+ years (2+ years with a PhD) of experience in model development, statistical work, data analytics or quantitative research

Shift:

1st shift (United States of America)

Hours Per Week: 

40