Senior Manager - Commercial Credit Model Development (Hybrid - See Description for Potential Locations)

M&T Bank•Bridgeport, CT

21d•$180,900 - $301,500•Hybrid

About The Position

The Senior Manager - Commercial Credit Model Development leads the strategic design, development, implementation, governance, validation support, maintenance, and enhancement of the Bank’s commercial risk rating and scorecard models. These models support credit risk management, portfolio monitoring, regulatory compliance, capital management, and other enterprise initiatives. The role establishes the long-term vision and roadmap for commercial credit risk modeling frameworks and provides subject matter expertise in commercial underwriting and risk quantification, particularly Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), and risk rating scorecards. It oversees the full model lifecycle, from development and calibration through performance monitoring, back-testing, implementation, documentation, governance, and continuous improvement. The Commercial Scorecard group supports enterprise decisions such as allowance levels, approval authority, asset quality metrics, and loss forecasting for the CCAR process. The role is highly technical and requires careful execution across multiple initiatives, the ability to analyze and communicate complex business problems, and collaborative use of analytics across functions and products. This is a hybrid position requiring in-office work four days each week. The preferred location is Bridgeport, Connecticut; other potential locations include Buffalo, Baltimore, Washington, Wilmington, Iselin, New York City, or another M&T corporate office. Depending on the selected candidate’s location, remote work may be possible.

Requirements

At least 10 years of relevant experience, including 5 or more years of prior management or supervisory experience.
PhD or master’s degree in mathematics, statistics, quantitative analysis, or another technical discipline; alternatively, a bachelor’s degree plus at least 12 years of relevant experience, or no degree plus at least 14 years of relevant experience.
Experience developing models using segmentation analysis, logistic regression, decision trees, and multivariate analysis.
Strong understanding of commercial loan and mortgage underwriting, loan structuring, and credit analysis.
At least 3 years of experience applying advanced programming and analytical skills using Python, R, SAS, SQL, AI/ML, data validation tools, Git, and cloud computing platforms to build, validate, and deploy quantitative risk models, automate analytics, and support credit risk decisions.
Strong analytical, financial, statistical, and model development skills.
Experience gathering, matching, and processing large datasets across continuous and categorical structured or unstructured data.
Familiarity with banking-sector model development and governance standards, especially for wholesale products and lending, including SR11-7, SR26-2, and OCC 11-12.
Working knowledge of Commercial & Industrial and Commercial Real Estate credit underwriting and quantitative risk analysis, including cash flow, borrowing base, and capital structure analysis.
Demonstrated experience conducting quantitative credit analysis and rating structured finance transactions, including ABS and other securitized products.
Sophisticated knowledge of PC, Core Bank process systems, databases, and statistical software.
Excellent verbal and written communication, cross-functional collaboration, and management skills.
Ability to communicate complex statistical concepts to broad audiences in non-technical terms.

Responsibilities

Lead development, implementation, and maintenance of commercial PD and LGD credit underwriting model frameworks using internal and external data, emerging technologies, and agile modeling principles.
Develop algorithms and tools to test model performance, robustness, stability, and ongoing monitoring, ensuring compliance with internal and external regulations.
Apply automation, machine learning, data frameworks, and implementation platforms to create scalable solutions for data mining, segmentation, back-testing, reporting, and monitoring.
Develop credit ratings for structured finance transactions through collateral analysis, cash flow modeling, and structural enhancement assessments.
Determine when model redevelopment or recalibration is needed due to changes in market conditions, regulations, or strategy, and guide redevelopment efforts.
Partner with Centralized Technology to integrate rating models into appropriate platforms and support stable data capture and delivery to end users.
Lead rating scorecard deployment and work with MROC on model communications, independent validation scheduling, committee presentations, communications with business lines and other stakeholders, and timely remediation of findings.
Explain proposed credit risk models, scorecards, solutions, strategies, benefits, limitations, assumptions, and requirements to internal customers, including executive management.
Build, manage, and develop a team of modelers and quantitative analysts, tracking their statistical modeling development in areas such as segmentation analysis, logistic regression, decision trees, and multivariate analysis.
Develop and maintain training for users of rating scorecards to support accurate and appropriate ratings.
Develop modeling strategies and techniques for commercial credit risk areas new to the organization and present findings to senior management.
Perform ad hoc analysis or projects as assigned by the Credit Risk Manager.
Adhere to applicable compliance and operational risk controls and company or regulatory standards and policies.
Exercise managerial authority over staffing, performance appraisals, promotions, salary recommendations, performance management, and terminations.
Directly manage 3–10 Quantitative Credit Risk Management Analysts and Modelers and potentially other Quantitative Risk Managers.