Senior Credit Modeling & Risk Analytics Lead

Wilmington Trust; New York (NY); Hybrid; USD 123,600 - 206,000; Full time

Job summary

Wilmington Trust seeks a seasoned quantitative risk professional to develop, implement, and maintain econometric models for credit, interest rate, and liquidity risk. You will lead research, run regressions, and work with large datasets in SQL/Python to inform risk strategy and capital planning.

The role requires mentoring others, presenting results to stakeholders, and ensuring model documentation and regulatory compliance.

Qualifications

• Bachelor’s degree with 6+ years of proven quantitative behavioral modeling experience, or a combination of higher education and work experience totaling at least 10 years with 6+ years in modeling.
• Experience with credit model development and with logistic/linear regression.
• 6+ years of experience with Python and data analysis tools.
• 6+ years of experience with SQL Server Management Studio.
• Strong ability to convey results through concise written and verbal communication, including charts and graphs.

Responsibilities

• Lead development of quantitative behavioral models for credit risk, interest rate risk, and liquidity risk management.
• Prepare, manage, and analyze large datasets for econometric models using SQL/Python.
• Run regressions and other analyses; communicate results to stakeholders and management.
• Develop, maintain, and manage model documentation and performance monitoring guidelines.
• Mentor and lead junior analysts; collaborate across risk management teams.

Skills

Quantitative modeling

Statistical analysis

Data visualization

Communication

Education

Bachelor's degree and 6+ years experience in quantitative modeling

Master's/ PhD preferred

Tools

Python

SQL Server Management Studio

Job description

Wilmington Trust seeks a seasoned quantitative risk professional to develop, implement, and maintain econometric models for credit, interest rate, and liquidity risk. You will lead research, run regressions, and work with large datasets in SQL/Python to inform risk strategy and capital planning.

The role requires mentoring others, presenting results to stakeholders, and ensuring model documentation and regulatory compliance.