Bank Of America Vice President Quantitative Finance Analyst 

United States, California, San Francisco 

169393539

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• 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.

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• 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.

If interested apply online at or email your resume to and reference the job title of the role and requisition number.

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1st shift (United States of America)