The company is seeking to improve its portfolio risk modeling and stress testing capabilities to address complex business challenges and regulatory requirements.
Requirements
- Credit risk modeling in consumer financial products
- Developing Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) models in at least one of the following: CCAR, CECL, or BASEL
- Using linear and logistic regression models for identifying relationships and predicting outcomes
- Model diagnostics to address multicollinearity, heteroscedasticity, and autocorrelation
- Coding in SAS
- Performing data analysis in Python using pandas and NumPy
- Using UNIX and Linux Shell Scripting to automate tasks, manage data, and integrate tools and processes
Responsibilities
- Lead the design, development and implementation of advanced portfolio risk models
- Oversee the preparation of comprehensive presentations of econometric models
- Conduct in-depth analysis of model performance and trends for strategic decision-making
- Lead team efforts with loss forecasting and business teams to address client issues in model construction
- Accurately translate regulatory requirements mandated for large financial institutions to design, modify and simplify model stress testing exercises
- Oversee testing, validation, and outcome analysis of models
- Identify model limitations, communicating findings to stakeholders
Other
- PhD in Finance, Mathematics, Mathematical Finance, Economics, Statistics, or related quantitative field of study plus three (3) years of experience
- Alternatively, a Master's degree in Finance, Mathematics, Mathematical Finance, Economics, Statistics, or related quantitative field of study plus six (6) years of experience
- Three (3) years of experience working for a global financial institution working in credit risk modeling
