Quantitative Finance Analyst - Global Markets Risk Analytics

Job Description:

Overview of Global Risk Analytics
Bank of America has an opportunity for a Quantitative Finance Analyst within our Global Risk Analytics (GRA) function. GRA is a sub-line of business within Global Risk Management (GRM).  GRA is responsible for developing a consistent and coherent set of models and analytical tools for effective risk and capital measurement, management and reporting across Bank of America. GRA partners with the Lines of Business and Enterprise functions to ensure that its models and analytics address both internal and regulatory requirements, such as quarterly Enterprise Stress Testing (EST), the annual Comprehensive Capital Analysis and Review (CCAR), and the Current Expected Credit Losses (CECL) accounting standard.  GRA models follow an iterative and ongoing development life cycle, as the bank responds to the changing nature of portfolios, economic conditions and emerging risks.  In addition to model development, GRA conducts model implementation, data management, model execution and analysis, forecast administration, and model performance monitoring. GRA drives innovation, process improvement and automation across all of these activities. 

Overview of the Team
Global Markets Risk Analytics (GMRA) is part of Global Risk Analytics (GRA). It responsible for developing, maintaining, and monitoring counterparty credit risk and market risk models. GMRA also develops analytical tools to support regulatory, audit, and internal risk management needs for Global Markets. This role sits within VaR Model Performance team (MP), which is responsible for monitoring and assessing the performance of Value at Risk (VaR), Risk Not in VaR (RNiV) and other ancillary models used across Global Markets. The responsibilities include supporting risk management in understanding the drivers behind material risk metric movement, the impact of model limitations, and working with the model development team to enhance model accuracy and the overall performance of the analytics platform.

Overview of the Role
As a Quantitative Finance Analyst on the VaR Model Performance team, your responsibilities will involve:
 

• Perform in-depth analysis on the Bank’s Value at Risk (VaR) model and Risks Not in VaR (RNiV) models employed for market risk using various quantitative tools such as backtesting, benchmarking, and sensitivity analysis.
• RNiV execution: Quantify the impact of model limitations both in terms of firm level capital and business level exposure by using bespoke tools to perform calculations
• Synthesize the overall holistic picture of model performance along with clear conclusions on overall accuracy and remediation areas as required and document continual ongoing monitoring reports.
• Communicate results of model performance analysis to model stakeholders including risk management, model development, model risk, senior management and our regulators.
• Support model development in analysis as required for remediation of model issues prior to their being taken live.
• Drive improvements to the model performance assessment tool set across all business areas through automation work, development of utilities, and enhanced visualization tools.

Position Overview
Responsible for independently conducting quantitative analysis and drawing conclusions. Responsible for developing analytic processes or systems approaches. Creates documentation for all activities and works with Process Engineering team in design of any system to processes developed. Incumbents possess excellent quantitative/analytic skills and a broad knowledge of financial markets and products.

Required Education, Skills, and Experience:

• Master’s degree and above (or equivalent), preferably in quantitative finance or a quantitative field
• Solid working experience (2 years +) in a related field (Market Risk, Middle Office, Counterparty Credit Risk).
• Broad financial product knowledge
• Experience in data analysis, with excellent research and analytical skills
• Proven programming skills (Python, R, or equivalent object-oriented programming) with keen sense of automation improvements where possible
• Good written and oral communication, interpersonal and organizational skills and ability to build and maintain relationships with personnel across areas and regions
• Ability to multitask with excellent time management skills
• Sense of focus and rigor in the completion of deliverables
• Pro-active behavior with capacity to seize initiative

Shift:

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