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Model Risk - Quant Modeling Lead - Vice President

J.P. Morgan

Overview Bring your expertise to JPMorganChase. As part of Risk Management and Compliance, you play a crucial role in maintaining JPMorganChase's strength and resilience. 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 Quant Model Risk Vice President in the Model Risk Governance and Review team, you will be responsible for assessing and mitigating the risks associated with complex models used for valuation, risk measurement, capital calculation, and decision-making purposes. You\'ll be at the forefront of innovation, driving continuous improvement in a dynamic and collaborative environment. This role also provides the opportunity to gain exposure to various business and functional areas, as well as collaborate closely with model developers and users. You will also have managerial responsibility to oversee, train and mentor junior members of the team. Job Responsibilities Perform thorough reviews of complex credit, interest rate, and equity pricing models, including valuation engines and reserve methodologies. Analyze the conceptual soundness, model design, and appropriateness of models for specific products and structures. Evaluate model behavior and ensure the suitability of pricing models and engines for their intended applications, identifying potential limitations and areas for improvement. Develop and implement alternative model benchmarks. Design and maintain robust model performance metrics to compare and monitor the outcomes of various models. Continuously evaluate model performance, ensuring models remain fit for purpose and compliant with internal and regulatory standards. Recommend enhancements and oversee remediation where necessary. Serve as the primary point of contact for the business regarding new model implementations and changes to existing models. Provide expert guidance on model usage, limitations, and governance requirements. Liaise effectively with model developers, Risk, and Valuation Control Groups. Offer guidance and support on model risk management, validation standards, and regulatory expectations. Manage and develop junior team members, providing mentorship, guidance, and support to foster their professional growth and enhance overall team performance. Required Qualifications, Capabilities and Skills Advanced degree (MSc, PhD, or equivalent) in a quantitative discipline such as mathematics, statistics, financial engineering, or related field. Advanced knowledge of probability theory, stochastic processes, statistics, partial differential equations, and numerical analysis, with demonstrated ability to apply these concepts to financial modeling and risk assessment. Deep understanding of option pricing theory and quantitative models for pricing and hedging derivatives, including familiarity with stochastic calculus and risk-neutral valuation. Strong analytical and problem-solving skills, with an inquisitive mindset and the ability to formulate insightful questions, identify model limitations, and escalate issues appropriately. Excellent written and verbal communication skills, with the ability to clearly explain complex quantitative concepts to both technical and non-technical stakeholders. Proficient programming skills in languages such as C/C++, Python, or similar, with experience implementing numerical algorithms and developing model prototypes. Demonstrated curiosity and ownership, with a strong willingness to work collaboratively within a team-oriented environment. Extensive experience in front office model development or in model review, validation, and governance within financial services, with a strong understanding of credit, interest rate, and equity pricing models. #J-18808-Ljbffr J.P. Morgan

Vacancy posted 5 days ago
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