Vice President, Quantitative Analyst - Risk & Margin (New York) Are you a quant with deep expertise in risk analytics, margin methodology development, and quantitative modelling? We're seeking a Vice President, Quantitative Analytics to join a Liquid Financing team, partnering closely with Risk stakeholders to develop and enhance client margin frameworks, exposure monitoring models, and risk methodologies across a range of financing products. Key Responsibilities • Develop, maintain, and enhance margin methodologies across Liquid Financing products. • Build quantitative models and analytics used to monitor client exposures and portfolio risk. • Partner with Risk and senior business stakeholders on risk and margin-related initiatives. • Deliver analytical solutions to support day-to-day risk management and strategic projects. • Drive model implementation and quantitative tooling using Python and modern development practices. Requirements • Strong experience within quantitative risk, margin, financing, prime brokerage, XVA, treasury, or related markets businesses. • Recent hands-on experience applying stochastic calculus, conditional probability, and quantitative risk modelling techniques in a commercial environment. • Demonstrable experience developing, enhancing, validating, or governing margin methodologies, including exposure modelling, stress testing, collateral analytics, initial margin, and/or variation margin frameworks. • Experience with fixed income and/or equity products and associated quantitative models. • Advanced Python programming skills and experience with object-oriented development. • Strong understanding of calculus, probability theory, statistics, and quantitative modelling. • Excellent communication skills with the ability to explain complex quantitative concepts to both technical and non-technical stakeholders. Preferred Experience • Prime Brokerage, XVA, Corporate Treasury, Repo, Margin Lending, Futures, or Equity Options experience. • Knowledge of margin methodologies, stress scenarios, and risk framework design. • Experience with AWS, Kubernetes, CI/CD practices, workflow automation, and databases. • Experience with Jupyter, Dash, APIs, and data visualisation tools. • Familiarity with AI-assisted software development tools This is an excellent opportunity for a hands-on quant who enjoys combining rigorous mathematical modelling with practical risk and margin management challenges.