Model Risk ManagerApply Now
- Requisition # 35036
- Job Type Day
- Location San Francisco, CALIFORNIA
- Date Posted 03/05/2021
Your potential. Your opportunity.
Serving as the model validation lead for credit loss statistical models including ratings, economic capital, and models used for Comprehensive Capital Analysis and Review (CCAR) and Dodd-Frank Act Stress Tests (DFAST) submissions; Independent testing and documenting validation results, including analyzing and interpreting statistical data, assessments of model conceptual soundness, evaluation of data and assumptions, testing model computational accuracy, and performing outcomes analysis; Managing the resolution of findings, recommending management action plans, and tracking remediation progress; Assisting in the development, maintenance and implementation of the Bank’s Model Risk Management Program utilizing statistical methods; Consulting with model users on the design of effective model operational controls; Interfacing with regulators from the Office of the Comptroller of the Currency (OCC) and Federal Reserve Bank (FRB); and contributing to regulatory bank exams by preparing materials regarding the results of statistical analysis for regulators, and presenting to various bank examiners as required; Giving industry presentations as required; and preparing, and presenting state-of-the-art modeling techniques at banking industry conferences; Coordinating third party consulting contracts for model validation related work.
Education: Master’s degree in Economics, Financial Engineering, Mathematics, Statistics or a related field (or foreign equivalent degree).
Experience: 5 years of experience in the banking industry in a risk management capacity building or validating statistical forecast models using SAS or R, including CCAR or DFAST models.
Location: San Francisco, CA
We are committed to leveraging the diverse backgrounds, perspectives and experience of our workforce to create opportunities for our people and our business; Equal Opportunity Employer: Minority/Female/Disability/Veteran.