Risk Management - Quant Modeling Lead - Vice President

JPMorgan Chase JPMorgan Chase · Banking · Jersey City, NJ +1 · Corporate Sector

The Quant Modeling Lead - Vice President role within JPMorgan Chase's Model Risk Governance and Review (MRGR) team focuses on the independent validation and risk governance of forecasting and scoring models, including those using advanced AI/ML techniques, for consumer banking applications. The role involves evaluating model conceptual soundness, performing independent testing, monitoring performance, and liaising with various internal and external stakeholders, including regulators.

What you'd actually do

  1. 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.
  2. 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.
  3. 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.
  4. Maintain model risk controls, help identify and escalate issues to ensure that their resolutions are sound and timely.
  5. 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.

Skills

Required

  • 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.

What the JD emphasized

  • advanced AI/ML techniques
  • model validation
  • risk governance
  • Bank regulators

Other signals

  • model validation
  • AI/ML techniques
  • risk governance