Risk Management - Quantitative Research Senior Associate

Job Responsibilities

• Design and implement enhancements to the counterparty credit risk framework, ensuring models remain robust, accurate, and aligned with evolving regulatory and business requirements
• Conduct quantitative analysis leveraging the firm's infrastructure to evaluate model performance and support methodological development
• Collaborate with risk and technology partners to jointly manage the full model lifecycle, from development through validation and production deployment
• Provide timely and accurate support for business requests, translating complex quantitative concepts into actionable insights for stakeholders
• Monitor ongoing performance of the calculation framework and contribute to governance processes that ensure model integrity and compliance
• Partner closely with Quantitative Research teams across global locations to share knowledge, align methodologies, and drive consistency
• Produce clear and thorough documentation of modeling choices, theoretical frameworks, testing procedures, and results to support transparency and auditability

Required Qualifications, Capabilities, And Skills

• Formal training or certification on data science concepts and 2+ years applied experience
• Advanced degree (PhD, MSc, or equivalent) in Engineering, Mathematics, Physics, Computer Science, or a related quantitative discipline
• Proficiency in Python, with the ability to write clean, efficient, and well-documented code
• Demonstrated experience in quantitative finance or applied mathematics, with the ability to translate theoretical concepts into practical solutions
• Strong analytical and problem-solving skills, with a track record of working through complex, ambiguous challenges
• Excellent communication and collaboration skills, with the ability to work effectively across technical and non-technical teams in a global environment

Preferred Qualifications, Capabilities, And Skills

• Experience in counterparty credit risk, including familiarity with exposure methodologies such as stressed exposure or potential future exposure
• Proficiency in C++, particularly in the context of quantitative or financial modeling applications
• Working knowledge of derivatives across multiple asset classes, including rates, credit, equities, or commodities
• Exposure to model governance, validation frameworks, or regulatory requirements related to counterparty risk
• Experience working in a cross-functional or globally distributed team environment