When applying, select your preferred top three home-base locations from among the Federal Reserve Banks. Each of the Banks offers its quantitative fellows unique opportunities.
For example, here’s the type of work previous fellows have done:
Atlanta:
- Conducted transaction testing models during the examinations of model risk management and business line reviews
- Developed bank-reporting tools related to risk identification and monitoring
- Used natural language processing to enhance efficiencies in examinations
Boston:
- Supported the development and maintenance of retail credit and pre-provision net revenue supervisory stress test models
- Conducted research on risks to financial stability
- Worked on the management, measurement, and understanding of risk associated with supervisory stress test models
Chicago:
- Worked on a variety of quantitative-related topics within the Wholesale Credit Risk Center
- Supported the development and maintenance of wholesale credit supervisory stress test models, in terms of both risk identification and measurement
- Contributed to horizontal examinations and surveillance work for wholesale credit portfolios
Cleveland:
- Reviewed models and technical aspects of supervisory work, such as model risk management, wholesale and credit models, and market risk
- Conducted the System’s main horizontal reviews
- Engaged with select research work, including an artificial intelligence initiative and machine learning projects
Dallas:
- Developed, maintained, and reviewed supervisory early warning models for bank risk
- Worked on Systemwide stress testing models, monitored banking conditions in the district, and participated in preparing materials for the briefings of the Dallas Fed’s president
- Developed a variety of additional tools using machine learning and natural language processing
Minneapolis:
- Assisted the System Model Validation group by validating supervisory stress test models
- Worked with the Centralized Production Unit on the implementation and production of supervisory stress test models
- Assisted on examinations focused on components of preprovision net revenue
New York:
- Worked on data visualization and model development projects related to global trading and counterparty credit markets
- Developed a custom web application to support stress testing operations
- Engaged in the explorations of machine learning and natural language processing applications to supervisory work
Philadelphia:
- Focused on retail portfolios, including the RADAR group that manages the System’s largest retail data repository
- Developed the retail supervisory model for DFAST
- Provided front office and back office support for supervisory activities and bank examinations in the district and conducted supervisory research
Richmond (Charlotte, NC):
- Contributed to supervisory model development in various risk areas, including operational risk and wholesale credit risk, as well as modeling the effect of the global market shock
- Supported the LISCC program in multiple risk areas, including operational risk, wholesale credit risk, counterparty credit risk, and market risk
- Assisted on bank examinations, focusing on model development and model risk management
San Francisco:
- Participated in the development and production of supervisory stress testing models
- Worked on data management and analytics, model development and coding, code review, and ongoing model monitoring
- Developed an expertise in market risk modeling, such as counterparty credit risk, for business-as-usual and stress testing applications
- Focused on developing supervisory tools and leveraging data science techniques to enhance efficiencies in examinations and develop techniques to quantify nonfinancial risk
St. Louis:
- Applied emerging technologies, including machine learning and robotic process automation, to improve operational efficiency
- Conducted research into the future of the community banking business model
- Explored issues related to household balance sheets and consumer affairs examination data