Cross-Margin Quantitative Model Developer (Python / Counterparty Risk)
Location: Charlotte (Hybrid – 3 days onsite)
Duration: 12-Month Contract (Extension Possible)
Overview
We are seeking a Quantitative Model Developer with deep expertise in cross-margining and counterparty credit risk (CCR) within capital markets.
This role focuses on enhancing and modernizing cross-margin risk models used across complex derivative portfolios. The ideal candidate combines strong mathematical modeling skills with hands-on Python development, and has experience working in prime brokerage or derivatives environments.
Key Responsibilities
Quantitative Modeling
-
Develop and enhance counterparty credit risk models (CCR)
-
Design and improve cross-margin methodologies
-
Derive and implement mathematical models and formulas
-
Identify gaps and improve legacy model frameworks
Product Coverage
-
Model exposure across:
-
Equity swaps
-
Commodities (metals, energy)
-
Convertible bonds
-
Technical Development
-
Build and maintain Python-based quant libraries
-
Develop prototypes and partner with engineering teams for production rollout
-
Utilize tools like GitHub Copilot for development efficiency
-
Write and optimize SQL queries for large datasets
Collaboration & Leadership
-
Partner with model owners, risk teams, and technology stakeholders
-
Translate business requirements into quant specifications
-
Mentor junior team members on modeling and cross-margin concepts
Operational Execution
-
Support high-priority, time-sensitive model requests
-
Deliver enhancements and validations aligned with business needs
Required Qualifications
-
Strong experience in cross-margining (prime brokerage or derivatives clearing)
-
Deep understanding of counterparty credit risk (CCR) models
-
Expertise in Python (quant library development)
-
Strong SQL skills
-
Advanced knowledge of:
-
Probability & statistics
-
Stochastic processes
-
Financial modeling
-
Preferred Qualifications
-
Experience with PFE, EE, EAD models
-
Background in prime brokerage or margin methodology design
-
Exposure to multi-asset derivatives (equities, commodities, structured products)
-
Experience using AI-assisted coding tools (e.g., Copilot)
Skill Breakdown
-
Cross-Margin Expertise: 50% (MOST IMPORTANT)
-
Quant / Math Modeling: 30%
-
Python / SQL: 20%
