Senior Credit Modeling Lead — Risk Analytics

Wilmington Trust; Woodbridge Township (NJ); Hybrid; USD 85,800 - 143,000; Full time

Job summary

M&T Bank is seeking a senior quantitative analyst in Buffalo, NY to build, implement, and monitor behavioral models for credit, interest rate, and liquidity risk. You will prepare large financial datasets, run econometric analyses, and present results to Treasury and Risk Management teams.

The role requires Python, SQL expertise, strong communication, and the ability to work in a collaborative, regulated environment. Hybrid in-office work four days weekly at multiple U.S. offices is expected.

Qualifications

• Bachelor’s degree and 2+ years of quantitative behavioral modeling experience, or 6+ years of related work/education
• Minimum 2 years’ Python experience
• Model development experience including credit models
• Logistic Regression experience
• Experience with SQL Server Management Studio
• Strong written and verbal communication with large data sets

Responsibilities

• Develop and maintain quantitative behavioral models for credit risk, interest rate risk, liquidity risk and capital planning
• Prepare and analyze large customer loan/deposit data for econometric modeling using SQL or similar tools
• Run regressions and econometric analyses; communicate results to Treasury and risk stakeholders
• Operate models in production; monitor performance and explain variances
• Create model documentation and validation support; collaborate with Model Risk Management
• Mentor and guide more junior analysts; contribute to cross‑functional projects

Skills

Python

SQL

Data analysis

Econometrics

Communication

Leadership

Model development

Logistic regression

Time series analysis

Education

Bachelor’s degree

Masters preferred

Tools

SQL Server Management Studio

Job description

M&T Bank is seeking a senior quantitative analyst in Buffalo, NY to build, implement, and monitor behavioral models for credit, interest rate, and liquidity risk. You will prepare large financial datasets, run econometric analyses, and present results to Treasury and Risk Management teams.

The role requires Python, SQL expertise, strong communication, and the ability to work in a collaborative, regulated environment. Hybrid in-office work four days weekly at multiple U.S. offices is expected.