Quantitative Model Developer

About the role

Develop, enhance, and maintain quantitative models for cross-margin methodologies, focusing on counterparty credit risk across equity options, swaps, metals, energy derivatives, and convertible bonds. Validate model assumptions, derive analytical formulas, and identify and resolve gaps in existing model implementations. Upgrade or replace outdated models using modern stochastic and capital markets techniques.

Responsibilities

• Lead development and integration of Python-based quant libraries for modeling and validation.
• Ensure robust prototype models can transition to production.
• Utilize AI-assisted coding tools (e.g., Copilot) and strong SQL skills for coding efficiency and large dataset manipulation.
• Collaborate across functions with model owners, business partners, technology teams, auditors, and project managers to translate business requirements into technical/model specifications and documentation.
• Coach and provide technical guidance to junior team members on modeling and cross-margin concepts.
• Respond rapidly to urgent requests for model enhancements driven by high-impact exposures in the CIB business, ensuring timely delivery of solutions and documentation.

Requirements

• Expert-level Python, AI-assisted coding tools, and advanced SQL.
• Strong numerical skills and experience with stochastic modeling and capital markets models.
• Ability to derive and implement mathematical formulas.
• Deep knowledge of cross-margining in prime brokerage/derivatives clearing.
• Solid background in probability, statistics, and stochastic processes.

Qualifications

• Experience with prime brokerage or margin methodology design.
• Experience with counterparty credit exposure models (e.g., PFE, EE, EAD).
• Familiarity with equities, commodities, energy, and structured derivative products.

Skills

• Cross-margin expertise (~50%)
• Mathematics/modeling (~30%)
• Coding (Python/SQL) (~20%)