Hybrid Credit Model Development Quantitative Analyst I – Commercial Small Business Portfolio

at M&T Bank

• Job title: Credit Model Development Quantitative Analyst I – Commercial Small Business Portfolio
• Job type: Full Time
• Experience level: Junior
• Salary: $62,200 - $103,600 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Python, SQL
• Location requirements: Hybrid, Buffalo, United States

About the role

• Quantitative Analyst developing econometric models for credit risk, liquidity risk, and capital planning at M&T Bank. Involves data analysis, model development, and compliance with regulatory standards.

Responsibilities

• Assists in 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.
• Assist in researching and developing quantitative behavioral models used for credit risk, interest rate risk and liquidity risk management, as well as balance sheet and capital planning, including but not limited to, 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 for statistical analysis in Structured Query Language (SQL) or similar tool to properly specify and estimate econometric models to understand customer or Bank behavior for purposes of interest rate, liquidity or stressed capital risk.
• Produce and 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 of model development activities to fellow team members, Treasury management and Bank-wide stakeholders, including the business lines and Risk Management colleagues to demonstrate key risk drivers and dynamics of model output.
• Execute models in 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 and explain variances.
• Identify risk and/or opportunities.
• Support development and maintenance of satisfactory model documentation, including process procedures and performance monitoring guidelines to serve as 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.
• Conduct business in compliance with regulatory guidance including SR (Supervision and Regulation Letters) 10-1, SR 10-6, SR 11-7, Enhanced Prudential Standards, etc.
• Adhere to applicable compliance/operational risk/model controls and other second line of defense policies 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.

Requirements

• Bachelor's degree from accredited four year institution, or in lieu of a degree, a combined minimum of 4 years’ higher education and/or work experience
• Proven experience in analyzing data sets and explaining results of analysis through concise written and verbal communication as well as charts/graphs
• Probability & Statistics knowledge (via work experience and/or education)
• Linear regression knowledge (via work experience and/or education)
• Bachelor’s degree in Statistics, Economics, Mathematics, Finance or related field in the quantitative social, physical, natural or engineering sciences, inclusive of proven coursework proficiency in statistics, econometrics, economics, computer science, finance or risk management
• Prior experience in banking and financial services industry ideal
• Credit model development, especially small business credit model development experience, is ideal
• One or more years of statistical analysis programming experience ideal
• Experience with pertinent statistical software packages such as SAS, Stata R or Python with Python experience being highly preferred
• Fluency and high proficiency in econometric/statistical techniques, especially time-series analysis and logistic regression, with logistic regression being ideal
• 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
• Advanced knowledge of pertinent spreadsheet, word processing and presentation software.

Benefits

• Health insurance
• Retirement plans
• Forty hours of paid volunteer time annually