Quantitative Analyst - Regulatory Capital and Counterparty Credit Risk

Citi's Capital Analytics team is looking for a quantitative analyst to develop and maintain the models, analytics, and production systems that power regulatory capital compliance across global markets. You'll work at the intersection of advanced mathematics, high-performance engineering, and front-office trading — helping trading teams understand and optimise the capital impact of their activity in real time. This role suits someone who thrives on rigorous quantitative problem-solving and wants their work to drive tangible business and regulatory outcomes.

Design, implement, and maintain cross-asset quantitative analytics supporting regulatory capital frameworks — including standardised approach for counterparty credit risk (SA-CCR) risk-weighted assets, resolution metrics, and G-SIB indicators — across global derivatives and financing portfolios, using Python and C++. Build and optimise capital computation engines and production workflows, ensuring scalability, robustness, and computational efficiency across daily global regulatory capital runs. Develop high-performance, trade-level attribution tools that give trading desks clear, actionable visibility into the capital cost and impact of their activity. Collaborate with traders, structurers, and quantitative analysts to deliver model insights and analytical support for capital-efficient structuring and pricing decisions. Partner with Technology to design and deliver production-grade batch systems that generate daily regulatory capital outputs for front-office, risk, resolution planning, and G-SIB reporting. Engage with control functions — including model risk management, market risk, and compliance — to ensure models are well-governed, thoroughly documented, and compliant with regulatory requirements. Assess risk-reward trade-offs in modelling and analytical decisions, reinforcing a culture of sound risk management and reputational awareness across the team. Communicate complex quantitative concepts clearly and concisely to a broad range of stakeholders, from technical specialists to senior trading and risk professionals. Required qualifications & skills: A master's or doctoral degree in mathematics, physics, engineering, computer science, quantitative finance, or a related quantitative discipline, or equivalent practical experience in a relevant field. Strong programming skills in Python and/or C++, with demonstrated ability to write clean, efficient, and production-quality code. Solid grounding in the mathematical and statistical methods relevant to quantitative finance, including probability theory, linear algebra, and numerical techniques. Knowledge of financial products across derivatives and financing markets, and familiarity with the quantitative methods used in pricing, risk measurement, and analytics. Clear, confident communication skills — both written and verbal — with the ability to explain complex technical material to audiences with varying levels of quantitative expertise. A rigorous, detail-oriented approach to model development, with a strong appreciation for governance standards, auditability, and the accuracy of regulatory outputs. Beneficial skills & qualifications: Knowledge of counterparty credit risk frameworks, including SA-CCR, resolution metrics, or G-SIB methodology. Experience building or working within regulatory capital systems or risk-weighted asset calculation engines. Exposure to front-office or trading environments, with an understanding of how capital constraints shape structuring and pricing decisions. Experience collaborating across quantitative and technology functions to deliver scalable, high-performance production systems. Familiarity with model risk management processes, including model validation, documentation standards, and regulatory review cycles.

You will have access to structured professional development, mentorship, and skill-building programmes designed to support