Credit Risk Model Development Quantitative Analyst II - Consumer Portfolio; Hybrid - see de

Work Location/Arrangement

This is a hybrid position requiring in‑office work four (4) days every week at an M&T office in Buffalo, NY;
Bridgeport, CT;
Wilmington, DE;
Baltimore, MD;
Washington, DC; or possibly NY, NY. If the final candidate is not near one of these locations, there may be a possibility for a remote arrangement.

Provides experienced support in the development and analysis of quantitative/econometric behavioral models used for credit risk, interest rate risk and liquidity risk management, as well as balance sheet and capital planning. Supports more experienced analysts and management in data analysis, model development efforts and ad‑hoc analysis as needed. Provides guidance and direction to less experienced personnel as needed.

• Assist in researching and developing quantitative behavioral models used for credit risk, interest rate risk and liquidity risk management, and balance sheet and capital planning, including 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 loan, deposit and/or financial data sets for statistical analysis in SQL or a similar tool to properly specify and estimate econometric models to understand customer or bank behavior for purposes of credit, interest rate, liquidity or stressed capital risk management.
• Run regressions (including time series and logistic regression), programming routines and other econometric analyses to specify models using appropriate statistical software; communicate results, including graphic and tabular forms, to team members, Treasury management and bank‑wide stakeholders, including business lines and Risk Management colleagues to demonstrate key risk drivers and dynamics of model output.
• Execute models in a 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 improve predictive results. Identify deviations from forecast/expectations, explain variances, and identify risks or opportunities.
• Develop and maintain satisfactory model documentation, including process narratives 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. Support engagements with Model Risk Management for model validation exercises.
• Provide guidance and direction to less experienced personnel regarding all aspects of data and financial analysis, and the development and management of predictive statistical models.
• Conduct business in compliance with regulatory guidance including SR 10‑1, SR 10‑6, SR 11‑7, Enhanced Prudential Standards, etc.; adhere to applicable compliance/operational/model risk controls and other second line of defense and regulatory standards, policies and procedures.
• Understand and adhere to the company’s risk and regulatory standards, policies and controls in accordance with the company’s Risk Appetite; identify risk‑related issues needing escalation to management.
• Promote an environment that supports belonging and reflects the M&T Bank brand.
• Maintain M&T internal control standards, including timely implementation of internal and external audit points together with any issues raised by external regulators as applicable.

The position serves as an experienced analyst in the use of statistical programming languages to analyze bank datasets and develop, implement and maintain behavioral models. It requires clear narratives, compelling data visualization and technical precision, both in‑person and in writing, to enable audiences to understand the analyses and forecasts. The role partners and collaborates with colleagues in related functions—Credit Risk Management, Asset Liability and Liquidity Management, Model Risk Management, and business lines—to implement and understand models for bank use.

It is highly technical, demands attention to detail, execution and…