Quantitative Finance Analyst

Description

Overview of Global Risk Analytics

Bank of America Merrill Lynch 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 these activities.

Overview of the Role

As a Quantitative Finance Analyst on the team, your main responsibilities will involve :

Development of wholesale credit risk models including loss forecasting, commercial scorecards, behavioral score, regulatory capital models.

Executing in-depth analysis of wholesale credit performance and financial data.

Preparing white papers for developed models.

Interacting with internal model risk management, addressing potential concerns, and remediating model related findings.

Supporting post implementation activities including ongoing monitoring review and interaction with various stakeholders.

Required Education, Skills, and Experience

• Master’s degree in Math, Economics, Statistics, Engineering, Finance, Computer Science or similar discipline
• 2+ years professional experience developing credit risk models
• Strong Programming skills e.g. R, Python, SAS, SQL or other languages
• Strong analytical and problem-solving skills
• Experience using and developing cross-sectional models
• Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences
• Ability to work in a highly controlled and audited environment

Desired Skills and Experience

• Experience in developing credit risk models
• Ability to extract, analyze, and merge data from disparate systems, and perform deep analysis
• Experience developing and maintaining complex databases and data sets
• Experience using data mining and other advanced analytical techniques to aggregate data for model development and / or to produce management reporting
• Experience with data analytics and visualization tools (e.g., Alteryx, Tableau, MicroStrategy)
• Experience with LaTeX

Shift :

1st shift (United States of America)

Hours Per Week :