Quant Modelling Associate

Are you seeking an exciting opportunity to become a part of a dynamic and expanding team in a fast-paced and challenging environment This unique position offers you the chance to collaborate with the Business team to provide a comprehensive view. As a Quant Modelling Associate within our Risk Management and Compliance team at JPMorgan Chase, you will have a crucial role in upholding the strength and resilience of the organization. Your expertise will be utilized to address challenges that impact the company, customers, and communities. You will be an integral part of the Model Risk Governance and Review (MRGR) team, which is responsible for independent model review and governance activities aimed at managing Model Risk. The MRGR Trading division focuses on valuation and risk-management models within the Corporate & Investment Bank, particularly focusing on Derivatives Instruments that involve complex and advanced modeling techniques. Your responsibilities will include evaluating the conceptual soundness of model specifications, assessing assumptions, verifying inputs, conducting testing, ensuring correct implementation, and reviewing the performance metrics and risk measures. You will conduct independent testing of models by replicating or creating benchmark models, design experiments to measure the potential impact of model limitations, and evaluate risks posed by non-transparent model parameters. Your role will also involve documenting model review findings, acting as a point of contact for model governance inquiries, providing guidance on model usage, and staying informed about performance testing outcomes for models in the coverage area. To qualify for this role, you are required to have a Master's degree in a quantitative discipline such as Math, Physics, Engineering, Computer Science, Economics, or Finance, with a minimum of 3 years of relevant working experience or a PhD. You should possess expertise in probability theory, stochastic processes, statistical modeling, economic modeling, partial differential equations, and numerical analysis. Proficiency in programming languages such as Python, R, Matlab, C++, or others is essential. Additionally, you must have a risk and control mindset, strong communication skills, excellent analytical abilities, and problem-solving skills. While knowledge of machine learning is not mandatory, it would be considered a plus for this role.,