Senior Quantitative Risk Modeler – CECL/CCAR

U.S. Bank; Warszawa; Hybrid; PLN 180,000 - 280,000; Full time

Job summary

U.S. Bank, including Elavon, seeks a Quantitative Model Analyst to lead development and implementation of expected loss forecasting models (PD/LGD/EAD) for CRE, C&I, or Small Business portfolios. You will ensure regulatory compliance and leverage forecasting methods while collaborating with risk teams.

The role requires strong modeling background, programming skills in Python/SAS/SQL/R, and experience with cloud platforms like Azure. Hybrid work with on-site requirements is anticipated.

Qualifications

• Master's Degree or PhD in a quantitative field such as computer science, data science, mathematics, or statistics.
• 5 or more years of experience in credit risk modeling and industry-standard approaches (e.g.PD, LGD, EAD).
• Deep understanding of banking, financial metrics, and credit risk management.
• Knowledge of banking regulation and requirements for stress testing and credit reserves.
• Programming experience in Python (preferred) or similar statistical software (e.g.R, SAS)
• Experience with cloud-based tools and infrastructure (Azure or others).
• Strong analytical and problem-solving skills, coupled with thoroughness and attention to detail
• Effective interpersonal, verbal, and written communication skills.
• Ability to prioritize work, meet deadlines, and work under pressure and independently while balancing multiple priorities in a dynamic and complex environment.

Responsibilities

• Model Development: Develop expected loss forecasting models (PD/LGD/EAD) with best practice and document model methodology, selection evidence, model performance testing for validation and regulatory review.
• Review and revise segmentation and modeling approach based on changes in business unit, portfolio or economic intuition.
• Analyze model metrics (e.g., accuracy, stability), identify issues, and recommend improvements.
• Coding: Use various programming languages (Python, SAS, SQL, R) in development and data analysis. Write and execute code in both local environment and cloud platforms (Azure or others).
• Model Review: Provide effective challenges to existing and new models to identify potential weak points and enhance model performance.
• CCAR/CECL Submission: Provide support for stress testing (CCAR) submission and CECL process; document associated portfolios analysis, respective overlays for emerging risks and reasonableness analysis; respond questions from senior management and regulators in a timely manner.
• Transformation: Leverage automation tools and AI to increase efficiency, reduce operational risk, and enhance usability and interpretability of results.

Skills

Python

SAS

SQL

R

Education

Master's Degree in quantitative field

Tools

Azure

Power BI

Git

Power Automate

Job description

U.S. Bank, including Elavon, seeks a Quantitative Model Analyst to lead development and implementation of expected loss forecasting models (PD/LGD/EAD) for CRE, C&I, or Small Business portfolios. You will ensure regulatory compliance and leverage forecasting methods while collaborating with risk teams.

The role requires strong modeling background, programming skills in Python/SAS/SQL/R, and experience with cloud platforms like Azure. Hybrid work with on-site requirements is anticipated.