Quantitative Model Developer, Counterparty Credit Risk Modeling (Contract) We are not accepting C2C or 1099 arrangements.

Location:

Charlotte, NC (Hybrid, 3 days per week in office)

Duration:

12-month contract with potential extension

Team:

Counterparty Credit Risk Modeling Benefits:

"Medical, dental, and vision insurance are available to qualified candidates who meet eligibility requirements." About the Role We are seeking a Quantitative Model Developer to support the development and enhancement of cross-margin counterparty credit risk models used across capital markets businesses. In this role, you will apply advanced quantitative techniques, software engineering practices, and financial modeling expertise to design, validate, and improve risk methodologies supporting equity options and other complex financial products. You will work closely with business stakeholders, model owners, technology teams, and quantitative analysts to deliver scalable modeling solutions and support the implementation of vendor-based models, including Hanweck methodologies. This position is well-suited for someone with deep cross-margin expertise, strong mathematical problem-solving skills, and advanced Python development experience. ResponsibilitiesQuantitative Modeling Develop, enhance, and maintain counterparty credit risk models supporting cross-margin methodologies. Analyze existing methodologies, identify model limitations, and recommend improvements. Derive and implement mathematical formulas for exposure measurement and risk assessment. Support modeling initiatives across asset classes, including: Equity derivatives and equity swaps Commodities, metals, and energy derivatives Convertible bonds and structured products Evaluate model assumptions and perform quantitative analysis to validate model performance. Software Development Design and develop Python-based quantitative libraries and analytical tools. Build prototypes and partner with engineering teams to implement production-ready solutions. Leverage AI-assisted development tools, including GitHub Copilot or similar technologies, to improve efficiency and automation. Develop and optimize SQL queries to analyze and process large datasets. Collaboration and Stakeholder Management Partner with business, risk, technology, and project management teams to define requirements and deliver solutions. Translate business objectives into quantitative methodologies and technical specifications. Communicate model design, assumptions, limitations, and results to technical and non-technical stakeholders. Mentor junior team members and provide guidance on quantitative modeling and cross-margin concepts. Risk and Operational Support Respond to time-sensitive model enhancement requests related to high-impact cross-margin exposures. Support model governance, documentation, validation, and implementation activities. Ensure timely delivery of model enhancements while maintaining high standards of accuracy and compliance. Minimum Qualifications Bachelor's degree in Mathematics, Statistics, Physics, Engineering, Finance, Computer Science, or a related quantitative field, or equivalent practical experience. 5 years of experience in quantitative analytics, quantitative modeling, or financial engineering. Experience developing quantitative models using Python. Experience working with SQL and large-scale datasets. Strong understanding of probability, statistics, and stochastic processes. Experience deriving and implementing mathematical models and formulas. Knowledge of cross-margin methodologies within prime brokerage, derivatives clearing, or capital markets environments. Strong analytical, problem-solving, and communication skills. Preferred Qualifications Advanced degree (Master's or PhD) in a quantitative discipline. Experience with counterparty credit risk modeling, including PFE, EE, EAD, or related methodologies. Experience designing margin or cross-margin methodologies for prime brokerage or clearing organizations. Familiarity with equity derivatives, commodities, energy products, and structured finance instruments. Experience integrating vendor models into risk management platforms. Experience using AI-assisted development tools such as GitHub Copilot. Experience working in highly regulated financial services environments. Key SkillsDomain Expertise Cross-margin methodologies Counterparty credit risk Prime brokerage Derivatives and capital markets Quantitative Skills Mathematical modeling Stochastic modeling Probability and statistics Model validation and enhancement Technical Skills Python SQL Quantitative libraries and analytics frameworks AI-assisted software development tools Additional Information Hybrid work arrangement with three days per week in the Charlotte office. Charlotte-based candidates are strongly preferred. Target implementation timeline supports a major options-related model deployment scheduled for April 2027. We are committed to building a diverse workforce and creating an inclusive workplace. We encourage applications from candidates with a wide range of experiences, backgrounds, and perspectives. Benefits Featured Medical, Dental , and Vision Insurance is offered to qualified candidates. Medical, dental, and vision insurance are available to qualified candidates who meet eligibility requirements.