Vice President, Data Scientist
HybridNew York City, New York, United States or New York, United States
Job Summary
Lead quantitative analytics and AI strategy for Pricing, XVA, Securities Finance, and AI-driven businesses by designing, implementing, and evolving pricing frameworks across asset classes. Partner with trading, risk, technology, and engineering teams to develop advanced models and AI-enabled solutions that support business growth and risk management. Apply machine learning and statistical techniques to solve complex problems, drive model governance, and ensure regulatory compliance. Act as a trusted advisor to senior stakeholders, translating quantitative concepts into actionable insights while providing technical leadership on model architecture and analytics strategy. Operate independently to deliver initiatives from research through production deployment, contributing to the advancement of quantitative best practices and thought leadership across the Markets team in New York.
Required Qualifications
- Significant experience in quantitative analytics, model development, quantitative research, machine learning, or quantitative platform delivery within financial markets
- Deep knowledge of derivative pricing, quantitative modelling, valuation methodologies, and risk analytics across one or more asset classes
- Strong understanding of XVA frameworks, collateral management, funding and capital optimisation concepts
- Experience applying machine learning, artificial intelligence, or advanced data science techniques to financial markets, trading, risk, or operational challenges
- Demonstrated track record of designing and delivering complex quantitative and AI-enabled solutions from concept through implementation and production deployment
- Strong stakeholder management and influencing skills, with the ability to partner effectively with senior business, risk, technology, and regulatory stakeholders
- Excellent problem-solving, analytical, and quantitative research capabilities
- Experience supporting model governance, validation, regulatory requirements, and AI risk management within a controlled environment
- Strong programming skills and experience working with modern quantitative, data science, and AI technology stacks
- Ability to operate independently, providing thought leadership and technical direction on strategically important initiatives without direct people-management responsibility
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