Quantitative Model Analyst
Core
Lead development and implementation of expected loss forecasting models (PD/LGD/EAD) for Commercial Real Estate, Commercial Industrial, and Small Business portfolios to ensure regulatory compliance.
Role type
Quantitative Model Analyst (Credit Risk)
Builds
Expected loss forecasting models and regulatory stress testing submissions
Domain
Banking / Credit Risk / Financial Services
Deliverable
production ML models
Required skills
Credit risk modeling (PD/LGD/EAD), Python, SQL, SAS, R, Azure, statistical methods, banking regulations, predictive modeling
Preferred skills
Machine learning concepts, automation tools, low-code platforms, data visualization, version control
Technologies
Python, SAS, SQL, R, Azure, Bash, Power Automate, Power Apps, Power BI, Git
Responsibilities
Develop expected loss forecasting models with best practices and document methodology; Review and revise segmentation and modeling approaches; Analyze model metrics and recommend improvements; Provide challenges to existing models to enhance performance; Support CCAR/CECL stress testing submissions and regulatory responses; Leverage automation tools to increase efficiency.
Seniority
Mid-Senior, hands-on IC