Risk Management - Quant Modeling Lead - Vice President

JPMorgan Chase
Jersey City, NJ, United States2026-04-14

About the job

Bring your Expertise to JPMorgan Chase. As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo and striving to be best-in-class.

Responsibilities

Focus on the review and risk governance of forecasting and scoring models (including models developed using traditional statistical methods as well as advanced AI/ML techniques) and used by Consumer and Community Banking (CCB) for stress testing, risk and regulatory capital measurement, allowance determination, new origination, etc.

Lead and engage in model validation activities, including (a) evaluate models’ conceptual soundness, reasonableness of assumptions, reliability of inputs, completeness of testing, outcome analysis and model performance (b) perform independent testing; measure the potential impact of model limitations, parameter estimation error or deviations from model assumptions; compare model outputs with empirical evidence and/or outputs from model benchmarks, and (c) monitor model performance on an ongoing basis.

Liaise with internal and external groups including Model Developers & Users (Risk, Finance, Operations and Marketing), Fair Lending, Technology, Control teams, Internal Audit and Bank regulators.

Maintain model risk controls, help identify and escalate issues to ensure that their resolutions are sound and timely.

Keep up with the latest developments in consumer banking (CCB and industry) in terms of modeling techniques (e.g., advanced AI/ML methodologies, LLMs), products, markets, models, risk management practices and industry standards.

Participate and actively contribute to the life and activities of MRGR CCB and MRGR more broadly.

Qualifications

Minimum

PhD or Master Degree in Statistics, Economics (with a focus on Econometrics), Data Science, Computer Science, Operations Research, Physics, Engineering, Applied Math or a quantitative science. In depth knowledge of probability theory, econometrics, statistics, numerical methods and machine learning, as well as experience with advanced AI/ML techniques.

5+ years prior experience in model development, model validation or quantitative research in financial institutions. Ability to conduct model validation end-to-end as an individual contributor.

Ability to ask incisive questions, assess issues and risks’ materiality. Inquisitive nature and strong analytical & problem solving abilities.

Knowledge of consumer banking; ability to understand the business and the regulation surrounding the business.

Verbal and written; ability to interface with stakeholders on model-related issues, write clear model validation reports; create presentations on model validation topics.

Proficient in statistical programming language such as Python or R; experienced in dealing with large data sets.

Preferred

No preferred qualifications listed.