Job Description

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%