$180,000-$220,000 per annum New York, United States PermanentVice 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:- ExperiencePrime 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.
