Lead a global team of quantitative experts to design, deliver, and govern best‑in‑class predictive models that power valuation, credit reserving, stress testing, budgeting, and risk assessment for CCB’s Auto and Business Banking lending portfolios. You will own the end‑to‑end modeling lifecycle and translate model insights into actions that shape portfolio strategy and risk outcomes. The CCB Portfolio Risk Modeling Center of Excellence brings together economists, statisticians, mathematicians, and analytics professionals to quantify and manage lending risks across Consumer & Community Banking. The team applies advanced methods to one of the world’s largest consumer lending datasets, partnering across JPMC to assess, measure, and manage critical risks across CCB portfolios.
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.
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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.
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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.