Senior Credit Modeling & Risk Analytics Leader

M&T Bank; Woodbridge Township (NJ); Hybride; USD 124 000 - 206 000; Plein temps

Résumé du poste

M&T Bank is seeking a senior developer in Treasury to support data, systems and forecasting for credit, interest rate risk, liquidity risk, CCAR stress testing and economic capital practices.

The role acts as a bank-wide expert in quantitative risk management, mentoring analysts and leading project teams when needed. Applicants should have strong modeling and SAS/Python/SQL skills and experience with large data sets.

Qualifications

• Bachelor’s degree in a quantitative field; minimum years of experience specified.
• Masters/PhD preferred with proven coursework in statistics/econometrics/economics.
• Strong proficiency in SAS, Python, and other statistical tools.
• Experience analyzing large data sets and communicating results clearly.

Responsabilités

• Lead research and development for data related to customers, portfolios and products; interpret results and present to senior management.
• Support model development for behavioral models across credit, liquidity and risk stress testing; engage with oversight groups.
• Explain model benefits, limitations and requirements to internal customers and partners.
• Collaborate to optimize pricing, underwriting or funding strategies to maximize profitability.
• Maintain model documentation and performance monitoring guidelines; provide guidance to junior staff.

Connaissances

Quantitative risk modeling

SAS

Python

R

SQL

Data analysis

Leadership

Formation

Bachelor’s degree in a quantitative field

Master’s degree or Doctorate in statistics/economics/finance

Outils

SQL Server Management Studio

Description du poste

M&T Bank is seeking a senior developer in Treasury to support data, systems and forecasting for credit, interest rate risk, liquidity risk, CCAR stress testing and economic capital practices.

The role acts as a bank-wide expert in quantitative risk management, mentoring analysts and leading project teams when needed. Applicants should have strong modeling and SAS/Python/SQL skills and experience with large data sets.