Description

The quantitative analyst will lead the design, testing, approval and implementation of the model monitoring for all credit risk models.  The analytics work will provide credible management direction to support business decisions and assist their understanding of the model risk, while ensuring full compliance with regulatory and internal policy requirements.  Consult with business line and other model stakeholders to understand their analytics needs; consult with IT and data teams to determine data source, and work with colleagues to ensure consistency of our approach with established standards.

• Lead efforts of model monitoring process through various approval committees (business approval committee, model risk committee, capital planning committee). 
• Drive agreement on model validation and monitoring approach and communicate quantitative methods and results to various stakeholders (model development, business units, model governance and approving committees, regulators).
• Lead best practice modeling techniques, ensure comprehensive documentation, and maintain best of class model monitoring and outcome analysis. 
• Coordinate the development, maintenance and enhancement of econometric expertise, stress testing for CCAR and CECL. 
• Identify and assess the differing risk factors/credit attributes in support of the business and model users.
• Provide timely remediation of data issues through effective root cause analysis.

Qualifications

•  5+ years of relevant experience from a Information Management, statistical, mathematical, scientific or financial background
•  3+ years relevant experience
• Advanced knowledge of SAS programming or other mainstream languages (i.e. SQL/ R/ Python), SAS certification a plus
• Ability to navigate multiple data warehouse platforms and different data environments 
• Understanding of Credit Risk Parameter Models PD/EAD/LGD and concepts of regulatory requirements for stress testing and allowance.
• Statistical model development and/or validation experience preferred
• Strong analytical and program solving skills are required to interpret data and draw conclusions
• Excellent written and verbal communications skills

Education:

• Undergraduate and 5+ years of relevant experience from a Information Management, statistical, mathematical, scientific or financial background
• Graduate Degree and 3+ years relevant experience

Hours and Work Schedule - 3 days in the office, 2 remote

• Hours per Week: 40
• Work Schedule: Monday-Friday

#LI-Remote