Cross Margin Quantitative Model Developer
Role details
Job location
Tech stack
Job description
- Develop, enhance, and maintain counterparty credit risk models related to cross margin methodologies
- Derive analytical formulas, validate assumptions, and identify gaps in existing implementations
- Improve or replace outdated models using modern stochastic and capital markets modeling techniques
- Support modeling across a range of complex financial products, including equity swaps, metals, energy derivatives, and convertible bonds
- Lead the build out and integration of Python-based quantitative libraries to support model development and validation activities
- Produce robust prototype models and partner with technology teams to transition them into production
- Communicate clearly with model owners, business partners, technology teams, auditors, and project managers
- Help translate business requirements into quant/model specifications and documentation
- Provide coaching and technical guidance to junior team members
- Respond quickly to urgent model requests driven by high-impact cross margin exposures
Requirements
This role involves enhancing and maintaining counterparty credit risk models with a focus on cross margining concepts in prime brokerage and capital markets. The ideal candidate will possess a strong mathematical foundation and hands-on Python engineering skills to develop methodologies, derive formulas, and improve model implementations. This position requires a strong sense of urgency due to the high-impact nature of cross margin exposure., * 5+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education
- Expert level Python with the ability to build, structure, and maintain quant libraries
- SQL expertise with the ability to query and manipulate large datasets
- Strong numerical skills and experience with stochastic modeling and capital markets models
- Ability to derive mathematical formulas and implement them programmatically
- Strong understanding of cross margining concepts in prime brokerage or derivatives clearing
- Ability to identify and correct model gaps, inconsistencies, or legacy issues
- Solid foundation in probability, statistics, and stochastic processes
Desired skills:
- Experience using AI-assisted coding tools (Copilot or similar)
- Experience in prime brokerage or margin methodology design
- Prior work with counterparty credit exposure models (e.g., PFE, EE, EAD)
- Familiarity with equities, commodities, energy, and structured derivative products