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. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities and shareholders every day.

One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We're devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being.

Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization.

• Conduct quantitative analytics projects related to the CVL portfolio risk management and CVL loss forecast submission (Baseline, CCAR, CECL).
• Identify requirements that improve the ability to generate insights and understanding of portfolio risk, model accuracy, and forecast reasonability.
• Develop and maintain new models, analytic processes or systems approaches in support of CVL risk management and loss forecasting.
• Document and communicate quantitative methods and operational processes as part of ongoing engagement with key stakeholders.
• Quantify long term and short-term risk under various stress scenarios, working with partner teams in quantifying loss forecasting risk on the CVL portfolio.
• Analyze large and complex financial dataset with programming tools of SQL, SAS, and R.
• Use visualization tools to develop drill-down dashboard capabilities and to summarize risk management trends for Executive stakeholders.
• Develop and analyze statistical models of linear regression, auto regression, and logistic regression to assess model diagnostic and model performance.
• Generate statistical analysis using SAS, SQL, and HIVE to support credit risk management, analytics and forecasting for Consumer portfolio(s).
• Use statistical tests, Kolmogorov-Smirnov test (KS), Receiver Operating Characteristic curve (ROC), Gini, and boosting techniques to assess overall model performance and predictive power of model attributes.
• Remote work may be permitted within a commutable distance from the worksite.

• Master's degree or equivalent in Finance, Statistics, Mathematics, Business Analytics, or related; and
• 2 years of experience in the job offered or a related quantitative occupation.
• Must include 2 years of experience in each of the following:
• Analyzing large and complex financial dataset with programming tools of SQL, SAS, and R;
• Using visualization tools to develop drill-down dashboard capabilities and to summarize risk management trends for Executive stakeholders;
• Developing and analyzing statistical models of linear regression, auto regression, and logistic regression to assess model diagnostic and model performance;
• Generating statistical analysis using SAS, SQL, and HIVE to support credit risk management, analytics and forecasting for Consumer portfolio(s); and,
• Using statistical tests, Kolmogorov-Smirnov test (KS), Receiver Operating Characteristic curve (ROC), Gini, and boosting techniques to assess overall model performance and predictive power of model attributes.
• The employer will accept pre- or post- Master's degree experience.