Credit Model Development Quantitative Analyst… at M&T Bank · Buffalo

Summary: M&T Bank is a financial institution seeking a Credit Model Development Quantitative Analyst II to provide analytical and technical support for credit risk model development and monitoring. The role involves collaborating with various teams to ensure models align with regulatory expectations and support strategic risk management objectives. Responsibilities: - Support the development, enhancement, and testing of credit risk models, including probability of default, loss forecasting, risk rating, and other borrower‑behavior models - Conduct statistical and econometric analyses using Python, SQL, and related tools to estimate, validate, and refine model components - Prepare, clean, and analyze large‑scale loan and customer datasets, ensuring data quality and readiness for modeling - Assist with model implementation and ongoing performance monitoring, identifying deviations and contributing to model improvements - Develop and maintain clear, comprehensive model documentation and performance monitoring reports - Communicate analytical findings through visualizations, presentations, and written summaries - Collaborate with Credit Risk Management, Model Risk Management, and business partners to ensure model alignment with regulatory expectations - Provide analytical support across the Bank and contribute to a collaborative, results‑focused environment Required Qualifications: - Bachelor's degree and a minimum of one year of proven quantitative behavioral modeling experience, or a combined minimum of five years of higher education and/or work experience, including at least one year of quantitative modeling experience - Minimum of one year of on‑the‑job experience using statistical software packages such as SAS, Python, or R - Strong Python skills required - Model development experience required, including familiarity with logistic and linear regression techniques - Minimum of one year of experience working in a data management environment such as SQL Server Management Studio - Minimum of one year of experience managing and analyzing large datasets, with the ability to communicate results clearly using written, verbal, and visual formats Preferred Qualifications: - Master's or Doctorate degree in Statistics, Economics, Finance, or a related quantitative field - Minimum of two years of statistical analysis or programming experience - Credit model development experience, with consumer, home secured, or small business modeling preferred - One or more years of hands‑on Python programming experience - Proficiency in econometric and statistical techniques, including panel‑data methods, and logistic regression - Knowledge of model risk management and validation practices, including familiarity with SR 11‑7 guidance - Ability to work independently and collaboratively within a team environment - Demonstrated leadership skills and a strong desire to learn and contribute to team objectives Required Skills: Credit risk modeling, Quantitative behavioral modeling, Python, SQL, Statistical software SAS, Statistical software R, Model development, Logistic regression, Linear regression, Data management, Statistical analysis, Econometric techniques, Model risk management