Head of CCB Auto and Business Banking Portfolio Risk Modeling

Job Responsibilities

• Lead and develop a high-performing global team building predictive risk models for CCB's Auto and Business Banking lending portfolios.
• Own the end-to-end modeling lifecycle (data sourcing, design, estimation, validation readiness, implementation, deployment, performance monitoring, and periodic recalibration).
• Ensure compliance with Firmwide model risk management standards and applicable regulatory expectations (e.g., SR 11-7/OCC 2011-12), with strong documentation, controls, and audit readiness.
• Deliver clear, decision-useful insights based on models and scenario analyses that inform credit strategy, reserving (e.g., CECL), stress testing, portfolio valuation, and budgeting.
• Advance the modeling roadmap by modernizing data pipelines, feature engineering, and model operations practices; drive process efficiency and reproducibility.
• Partner with Product, Risk, Finance, Technology, and Model Risk teams to align models with business objectives and ensure robust change management and governance.
• Establish model monitoring frameworks, performance thresholds, and action plans; proactively identify model, data, or process risks and drive remediation.
• Recruit, mentor, and retain talent; promote a culture of scientific rigor, delivery excellence, and inclusive leadership.

Required Qualifications, Capabilities, And Skills

• Ph.D. (or comparable advanced degree) in Economics, Statistics, Operations Research, Mathematics, or a related quantitative field; or equivalent experience.
• 10+ years building and deploying predictive risk models for consumer lending portfolios, with deep domain knowledge in auto and business banking credit.
• 5+ years leading and developing high-performing quantitative teams.
• Expertise across advanced modeling methods (e.g., parametric and non-parametric regression, time series, survival/PD-LGD-EAD frameworks, machine learning).
• Proficiency in Python and/or R; familiarity with SAS; strong SQL and experience with large-scale datasets.
• Demonstrated ability to communicate complex analytics succinctly and influence senior stakeholders.
• Strong analytical judgment and problem solving; track record of improving processes and controls.

Preferred Qualifications, Capabilities, And Skills

• Experience with CECL/allowance modeling, capital stress testing, and scenario design.
• Familiarity with model risk governance, validation expectations, and audit processes.
• Experience with modern data and model operations tooling (e.g., Spark, Git, CI/CD, workflow orchestration) and collaboration with Technology/Engineering teams.
• Exposure to cloud-based analytics environments and secure model deployment at scale.