Head of CCB Auto and Business Banking Portfolio Risk Modeling

JPMorgan Chase & Co.; Plano (TX); On-site; USD 190,000 - 270,000; Full time

Job summary

A major finance institution is seeking a leader for their quantitative modeling team. The role entails managing the entire modeling lifecycle to develop predictive models for Auto and Business Banking portfolios. With over 10 years' experience in consumer lending risk modeling and strong leadership in quantitative teams, candidates should be proficient in Python and/or R. The position requires a Ph.D. or equivalent in a quantitative field and aims to ensure compliance with firmwide standards while driving innovative risk assessment solutions.

Qualifications

• Ph.D. in Economics, Statistics or related field or equivalent experience required.
• 10+ years in predictive risk modeling for consumer lending.
• Expertise in advanced modeling methods and large-scale datasets.
• Expertise across advanced modeling methods (regression, time series, survival/PD-LGD-EAD, ML).
• Proficiency in Python and/or R; familiarity with SAS; strong SQL; large-scale data experience.

Responsibilities

• Lead a global team to build predictive models for CCB's Auto and Business Banking.
• Own the modeling lifecycle from design to deployment and monitoring.
• Ensure compliance with model risk management standards.
• Deliver insights informing credit strategy, reserving (CECL), stress testing, and budgeting.
• Advance the modeling roadmap by modernizing data pipelines and model ops; drive reproducibility.
• Partner with Product, Risk, Finance, Technology, and Model Risk to align models with business objectives.
• Establish model monitoring frameworks, thresholds, and remediation plans.
• Recruit, mentor, and retain talent; foster scientific rigor and inclusive leadership.

Skills

Predictive modeling

Statistical analysis

Team leadership

Risk assessment

Machine learning

Education

Ph.D. in quantitative field

Tools

Python

R

SQL

SAS

Job description

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 operationspractices; 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.