Job Description:

Job Description

Bank of America Merrill Lynch has an opportunity for a Sr. Quantitative Financial 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 Consumer Loss Forecasting
The Consumer Loss Forecasting (CLF) team is part of Global Risk Analytics (GRA). CLF provides analytical insights, enabling improved Credit Risk management. The primary delivery vehicle is through consumer loss forecasts. , These forecasts are utilized for allowance setting, financial planning, Comprehensive Capital Analysis & Review (CCAR) submission, and other business decision-making. In order to deliver these insights, the team:

Conducts research and analysis to improve understanding and assessment of loan portfolios, models used and forecast results
Develops, maintains, and executes select models, quantitative methods, assumptions utilized in loss forecasting; and associated tools and reports
Manages related infrastructure and processes that enable forecasts and analytics together with Operations
Partners with Consumer lines of business, and front line Risk, Allowance, and Finance teams to ensure consistency and appropriateness of the team s various processes

This role plays a critical part in the Bank s stress testing, financial planning, and risk management activities. It requires a strong understanding of consumer credit business with the ability to apply this knowledge to data and quantitative analysis, combining business acumen with analytical and statistical skills to assess, explain, detect, quantify risks and uncertainties, communicate key insights and discoveries to broader loss forecast community on material discoveries and drive well-informed risk management decisions.

The Sr. Quantitative Financial Analyst interacts with a wide variety of stakeholders including risk managers, model developers, statisticians and data analysts. The Analyst will

• partner with risk managers to identify financial industry changes that could have material credit implications and prioritize risk concerns for analytical inquiries
• partner with data analysts and machine learning experts in designing and conducting data researches and statistical analyses to deepen understanding of credit behaviors and provide answers to key risk concerns
• summarize and present key insights and discoveries found through a combination of data researches and statistical/machine learning analyses, regarding new risk drivers, emerging risk indicators, material credit behaviors or change in risk behaviors to broader loss forecasting community
• Prototype and enhance portfolio monitoring through incremental inclusion of newly found meaningful risk metrics
• Review portfolio monitoring report, identify key trends and status, translate into stories and portfolio health insights, and report back to key stakeholders

Required Skills
Must have at least 5 years of experience in managing front line and/or second line of credit businesses e.g. portfolio acquisition, credit underwriting, credit risk management, loss detection and mitigation strategies
Must have strong communication and presentation skills, with the ability to adjust to both technical and executive audiences, explain complex statistics/technical concepts in laymen terms

Experience in data science, quantitative models, and/or machine learning methods with excellent analytical skills
Proficiency with Tableau, MS Excel, and PowerPoint

Bachelor's degree

Desired Skills
Hands on consumer behavior analytics or risk modeling experience in a financial institution
Programing skills (Python, R, SQL, LaTeX)
Experience meeting with internal / external examiners and responding to questions and required actions
Experience with DFAST / CCAR

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