Quantitative Analytics Specialist 4
Anveta
- Charlotte, North Carolina, United States
- Charlotte, North Carolina, United States
Über
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 Improve or replace outdated models using modern stochastic and capital markets modeling techniques.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:
Metals Energy derivatives Convertible bonds
Technical Development:
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.
Cross-Functional Collaboration:
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.
Operational Readiness:
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.
Required Technical Skills:
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.
Required Quantitative Skills:
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.
Skill Weighting:
Cross-margin expertise: ~50% Mathematics/modeling: ~30% Coding (Python/SQL): ~20%
Preferred Qualifications:
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.
In this contingent resource assignment, candidate may:
Consult on complex initiatives with broad impact and large-scale planning for Quantitative Analytics. Review and analyze complex multi-faceted, larger scale or longer-term Quantitative Analytics challenges that require in-depth evaluation of multiple factors including intangibles or unprecedented factors. Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables. Strategically collaborate and consult with Client personnel
Required Qualifications:
5 plus years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
Note:
Team: Contingent Solutions – Counterparty Credit Risk Modeling OFFER BACKOUT, NEED IMMEDIATE BACKFILL
177271 A Submission format – please complete in full: First Middle Last Name Skill Highlights- please indicate the # of years on each of the following skills:
Cross-margin expertise: ~50% Mathematics/Data modeling: ~30% Coding (Python/SQL): ~20%
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.
Sprachkenntnisse
- English
Hinweis für Nutzer
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