The Manager, Commercial Scorecard & Risk Rating Modeling is responsible for leading the strategic design, development, implementation, governance, validation support, maintenance, and ongoing enhancement of the Bank’s Commercial Risk Rating and Scorecard Models used for credit risk management, portfolio monitoring, regulatory compliance, capital management, and other enterprise-wide initiatives. Establishes the long-term vision and roadmap for commercial credit risk modeling frameworks, ensuring models remain robust, predictive, compliant, and aligned with evolving business objectives and regulatory expectations. Provides subject matter expertise and leadership for the Bank’s commercial underwriting and risk quantification models, with particular focus on Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), and risk rating scorecards.  Oversees the full model lifecycle, including model development, calibration, performance monitoring, back-testing, testing, implementation, documentation, governance, and continuous improvement.

The Commercial Scorecard group is a critical component of the Credit Risk Department.  Risk Ratings are utilized in many areas of the bank and are a key driver of many enterprise level decisions such as the level of the Allowance for Loan and Lease losses, determining levels of Approval Authority and Asset Quality Metrics.   This is mission critical information that is utilized internally across the organization and externally by the Bank Examiners, Outside Accountants, rating agencies and the investment community.   The ratings are also a key input into the loss forecasting models utilized for the CCAR process.  Loss Forecasting models are used in Capital Plan submissions that are a critical component of sound Bank management and are subject to regulatory scrutiny under DFAST regulations.

This role is highly technical in nature and requires demonstrated attention to detail execution and follow up on multiple initiatives within the Credit Risk department. The ability to identify, analyze, rationalize and communicate complex business problems and recommend solutions is a key factor of success in this role. Success in this role requires the ability to use analytics in a collaborative effort across multiple functions and products to derive optimum solutions to business problems.

Primary Responsibilities:

• Oversee the development, implementation, and maintenance of the framework for Commercial PD and LGD credit underwriting models for the institution using internal/external data/environment, next gen technologies, and agile modeling principles
• Develop algorithms and tools for testing overall performance, robustness, stability, and ongoing monitoring of the model to ensure compliance of models to internal/external regulations.
• Adapt automation and machine learning techniques, data frameworks, and implementation platforms to build scalable modeling solutions across data mining, segmentation, back testing, reporting and ongoing monitoring areas to speed up the model development process.
• Develop credit ratings to structured finance transactions, by performing collateral analysis, cash flow modeling, and structural enhancement assessments
• Determine when redevelopment or recalibration is needed based on changes in market conditions/regulations/strategy and guide the redevelopment efforts
• Partner with Centralized Technology to ensure that Rating models are fully integrated into the appropriate platform which allows seamless delivery to the end user while providing for a stable and robust data capture process. 
• Display organizational subject matter expertise on Rating scorecard deployment while partnering with MROC to communicate all models, ensure independent validation is scheduled, present models to committees, communicate to business lines, legal, compliance, risk committee, and all interested parties. Remediate any internal/external findings on a timely basis.
• Interface with a wide range of internal customers, including executive management, to explain the benefits, limitations, assumptions and requirements for proposed credit risk models, and scorecards, solutions, and strategies to implement these models as applicable.
• Build, manage and develop a team of modelers and quantitative analysts and track the development of their statistical modeling acumen in areas including (but not limited to) segmentation analysis, logistic regression, decision trees, and multivariate analysis.
• Develop and maintain a regimen of training to all users of the Rating scorecards to ensure that accurate and appropriate ratings are assigned. 
• Develop strategies and techniques for modeling commercial credit risk in areas new to the organization. Analyze and present findings to Senior Management.
• Execute ad hoc analysis or projects as assigned by the Credit Risk Manager.
• Adhere to applicable compliance/operational risk controls in accordance with Company or regulatory standards and policies.
• Exercise usual authority of a manager concerning staffing, performance appraisals, promotions, salary recommendations, performance management, and terminations.

Supervisory/ Managerial Responsibilities:

Direct management responsibility for 3 – 10 Quantitative Credit Risk Management Analysts and Modelers.  May have direct management responsibility for other Quantitative Risk Managers

Education and Experience Required: 

• Ten (10) or more years of relevant experience (inclusive of 5+ years of previous management/supervisory).

• PhD or master’s degree in mathematics, Statistics, Quantitative Analysis or another technical discipline or in lieu of Master’s degree, Bachelor’s plus 12 or more years of relevant experience or in lieu of no degree, 14 or more years of relevant experience.

• Experience developing models using segmentation analysis, logistic regression, decision trees, and multivariate analysis.

• A strong understanding of Commercial Loan and Mortgage underwriting, loan structuring, and credit analysis

• 3+ years of experience in applying advanced programming and analytical skills using Python, R, SAS, SQL, AI/ML, data validation tools, Git, cloud computing platforms to build, validate, and deploy quantitative risk models, automate analytics, and support strategic credit risk decision making

• Quantitative skills including strong analytical, financial, statistical, and model development skills.
• Track record of gathering, matching, and processing large data sets across continuous/categorical (structured or unstructured data
• Familiarity with model development and governance standards across the banking sector, especially related to wholesale products and lending (SR11-7, SR26-2, OCC 11-12)

• Working knowledge in Commercial & Industrial (C&I) and Commercial Real Estate (CRE) credit underwriting and quantitative risk analysis including cash flow, borrowing base analysis and capital structure analysis

• Demonstrated experience conducting quantitative credit analysis and rating of structured finance transactions, including ABS and other securitized products
• Sophisticated knowledge of PC, Core Bank process system, database, and statistical software
• Excellent Verbal and written communication, cross functional collaboration, and management skills
• Ability to communicate complicated statistical concepts to a broad audience in a non-technical manner.