Cross‑Margin Quantitative Model Developer
Job Description
JOB-247878 Cross‑Margin Quantitative Model Developer - 233775-1
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Client: Wells Fargo
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Location: Charlotte, NC 28202
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Schedule: Hybrid – 3 days per week in-office
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Duration: 12 months with potential to extend
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Interview: 30 min MS Teams call, possible 2nd round
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No Corp to Corp.
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Job Description: Cross‑Margin Quantitative Model Developer
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Primary Focus: Vendor-model development (Hanweck) for equity option pricing, volatility surface, and stressed or shocked-scenario P&L. The go live for options (which this risk model will support) is next April 2027.
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Team: Contingent Solutions – Counterparty Credit Risk Modeling
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Overview
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We are seeking a highly analytical Quantitative Model Developer with strong Python engineering skills and deep familiarity with cross‑margining concepts within prime brokerage and capital markets. This role focuses on enhancing and maintaining counterparty credit risk models—not pricing or market risk models—with an emphasis on mathematical rigor, cross‑product methodology development, and hands-on coding.
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The ideal candidate has a strong mathematical foundation, the ability to derive formulas, identify methodological gaps, and improve model implementations. You will work closely with junior team members, business partners, model owners, technology stakeholders, and project management groups.
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Because cross‑margin exposure plays a significant and high-impact role in CIB markets, this position requires a strong sense of urgency and responsiveness to ad hoc model requests.
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Key Responsibilities
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- Modeling & Quantitative Analysis
- 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:
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- Equity swaps
- Metals
- Energy derivatives
- Convertible bonds
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Technical Development
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- 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.
- Utilize generative AI development tools (e.g., Copilot) to increase coding efficiency and automation.
- Collaborate on database queries using strong SQL expertise.
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Cross‑Functional Collaboration
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- 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 on both modeling and cross‑margin concepts.
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Operational Readiness
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- Respond quickly to urgent model requests driven by high-impact cross‑margin exposures in the CIB business.
- Ensure timely delivery of model enhancements, documentation, and validations.
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Required Technical Skills
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- Python (expert level) – ability to build, structure, and maintain quant libraries.
- Experience using AI-assisted coding tools (Copilot or similar).
- SQL expertise – ability to query and manipulate large datasets.
- Strong numerical skills and experience with stochastic modeling and capital markets models.
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Required Quantitative Skills
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- 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.
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Skill Weighting
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- Cross‑margin expertise: ~50%
- Mathematics/modeling: ~30%
- Coding (Python/SQL): ~20%
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Preferred Qualifications
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- 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.
- Candidates located in Charlotte are strongly preferred; two existing team members are based here.
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