Quant Modeling Lead - Model Risk Governance Review - Vice President

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.

As a VP within the MRGR Asset Management team, you will own assigned model reviews, develop benchmark tools for independent testing, and assess ongoing model performance within the Asset Management business context. You will apply technical expertise and intellectual rigor to assess conceptual soundness, evaluate assumptions and implementation, and identify risks arising from individual models and model-to-model interactions. As an individual contributor, you will deliver high-quality validation reports, provide effective independent challenge to model developers and users, and communicate material findings and limitations to senior stakeholders. You will collaborate with colleagues across locations.

Model Risk Governance Review is a global team of modeling experts within the firm’s Risk Management and Compliance organization. The team is responsible for conducting independent model validation and model governance activities to help identify, measure, and mitigate Model Risk in the firm. The objective is to ensure that models are fit for purpose, used appropriately within the business context for which they have been approved, and that model users are aware of the model limitations and how they could impact business decisions.

Job responsibilities

• Assess Asset Management models against robust model development and testing standards, and contribute to enhancements in validation practices.
• Independently evaluate soundness of model design, reasonableness of assumptions, reliability of inputs, completeness of testing, correctness of implementation, and suitability of performance metrics.
• Identify weaknesses, limitations, and emerging risks through risk assessments, hands-on independent testing, development and implementation of benchmark models, and evaluation of ongoing monitoring.
• Own assigned model risk assessments, document high-quality validation reports, and communicate findings, limitations, and their business implications to senior internal and external stakeholders, as appropriate.
• Support model-related audits and regulatory examinations by explaining review conclusions and providing clear supporting analysis and documentation.
• Stay abreast of industry best practices, regulatory developments, and modeling advancements relevant to Asset Management, and incorporate them into independent assessments and validation methodologies.
• Manage assigned review deliverables and priorities independently, collaborating with model developers, users, and MRGR colleagues to resolve findings and escalate material issues appropriately.
• Proven ability to deliver complex quantitative work independently and collaborate effectively across multiple locations and geographic time zones.
• Ability to engage with senior business stakeholders and model developers and challenge them effectively.

Required qualifications, capabilities, and skills

• A PhD or Master’s degree in a quantitative field such as Mathematics, Physics, Engineering, Computer Science, Economics or Finance is required.
• 3+ years of experience in model validation or front office model development roles. 
• Strong verbal and written communication skills, with the ability to interface with other functional areas in the firm on model-related issues and write high quality technical reports.
• Deep understanding of pricing and risk management models – Requires understanding of derivative pricing and stochastic calculus.
• Deep understanding of standard statistical techniques for use in testing
• Ability to implement benchmarking models in Python, R, or equivalent.
• Risk- and control-oriented mindset: ability to ask incisive questions, assess the materiality of model issues, and escalate issues appropriately.
• Strong project management and organizational skills: flexible and adaptable to shifting priorities to achieve the most effective results.
• Ability to work in a fast-paced, results-driven environment.

Preferred qualifications, capabilities, and skills

• Prior experience developing, validating, or working with models used in Asset Management is highly desirable. The range of models covers the full spectrum of models – from Factor models for alpha generation and risk measurement, portfolio optimization, securities and derivative pricing and risk analytics to VaR and counterparty credit.
• Hands-on experience with standard Machine Learning models, including Boosted Trees, Neural Networks, SVM, and LLM (e.g. BERT).
• Experience of working with dedicated ML packages, such as TensorFlow or similar, as well as data processing and numeric programming tools (NumPy, SciPy, Pandas, etc.).