Credit Model Development Quantitative Analyst I- HELOC & Residential Mortgage (Hybrid - see description for potential locations)

Primary Responsibilities

Aid in the creation and analysis of quantitative/econometric behavioral models for credit risk, interest rate risk, and liquidity risk management, as well as balance sheet and capital planning. This includes loan delinquency, default and loss models, loan prepayment and utilization models, deposit attrition models, and financial instrument valuation methods.

Prepare, manage, and analyze large customer loans and deposit data sets using SQL or similar tools to specify and estimate econometric models for understanding customer or Bank behavior for interest rate, liquidity, or stressed capital risk.

Develop and execute models in the production environment; communicate analytical results to Bank-wide stakeholders. Track portfolio performance, model performance, campaign tracking, and risk strategy results. Incorporate observations and data into existing models to enhance predictive accuracy. Identify deviations from forecasts and explain variances. Identify risks and opportunities.

Create and maintain satisfactory model documentation, including process procedures and performance monitoring guidelines, to serve as a reference source. Provide financial analysis and data support to other groups/departments across the Bank as required. Engage with colleagues in Model Risk Management for model validation exercises.

Comply with regulatory guidance including SR letters, enhanced prudential standards, and adhere to compliance/operational risk/model controls and other second line of defense policies and procedures. Promote a supportive work environment that reflects the M&T Bank brand. Maintain M&T internal control standards, including addressing internal and external audit points as applicable.

Scope of Responsibilities

The role involves using statistical programming languages to analyze Bank datasets and develop, implement, and maintain behavioral models. Effective communication of analyses through clear narratives, compelling data visualization, and technical precision is crucial.

Collaborate with colleagues in Asset Liability and Liquidity Management, Model Risk Management, and business lines to implement and understand models for Bank use. The role is highly technical, requiring attention to detail, execution, and follow-up on multiple initiatives within Treasury and across the Bank.

Education and Experience Required

• Bachelor's degree from an accredited four-year institution, or a combined minimum of 4 years’ higher education and/or work experience
• Proven experience in analyzing data sets and explaining results through concise written and verbal communication, as well as charts/graphs
• Model development experience

Education and Experience Preferred

• Bachelor’s degree in Statistics, Economics, Mathematics, Finance, or related field with proven coursework proficiency in statistics, econometrics, economics, computer science, finance, or risk management
• Prior experience in banking and financial services industry
• One or more years of statistical analysis programming experience
• Experience with pertinent statistical software packages such as SAS, Stata, R, or Python (Python experience is highly preferred)
• Advanced knowledge of econometric/statistical techniques, especially linear regression and logistic regression
• Proven track record for working independently, within a team environment, exhibiting leadership, and a strong desire to learn and contribute to a group
• Minimum of 1 years' proven quantitative or data-oriented experience, including on-the-job use of statistical data analysis and data management environment such as SQL