Credit Risk Modeler II, Quant Analytics

Wilmington Trust; Wilmington (DE); Hybrid; USD 72,000 - 119,000; Full time

Job summary

M&T Bank in Buffalo, NY seeks an experienced quantitative analyst to develop and implement behavioral models for credit, interest rate and liquidity risk. You will work with large datasets, run econometric analyses and communicate results to Treasury, Risk Management and business lines.

The role requires strong Python skills, experience with SAS/R/Stata, and solid data management capabilities. Hybrid in-office work four days per week is expected, with potential remote arrangements.

Qualifications

• Bachelor’s degree required; quantitative modeling experience preferred.
• 1+ year proven quantitative behavioral modeling experience.
• 1+ year experience with SAS, Python, Stata, or R.
• Strong Python skills are required.
• Model development experience with logistic and linear regression.
• Experience with data management environments such as SQL Server.

Responsibilities

• Research and develop quantitative behavioral models for credit, interest rate, and liquidity risk management.
• Prepare and analyze large loan/deposit datasets using SQL or similar tools.
• Run regressions and econometric analyses; communicate results clearly to stakeholders.
• Execute models in production and monitor model performance.
• Develop model documentation and performance monitoring guidelines.
• Collaborate with Risk Management and business lines to implement models.

Skills

Python

SAS

Stata

R

Education

Bachelor’s degree in a quantitative field

Master’s degree in Statistics/Economics/Finance

Tools

SQL

SQL Server Management Studio

Job description

M&T Bank in Buffalo, NY seeks an experienced quantitative analyst to develop and implement behavioral models for credit, interest rate and liquidity risk. You will work with large datasets, run econometric analyses and communicate results to Treasury, Risk Management and business lines.

The role requires strong Python skills, experience with SAS/R/Stata, and solid data management capabilities. Hybrid in-office work four days per week is expected, with potential remote arrangements.