The Counterparty Credit Risk Quant Development Team at Citi is responsible for developing cutting-edge analytical models for derivatives risk and exposure calculations Firm-wide. This role aims to contribute to the research, coding, testing, documentation, and delivery of these models for internal and regulatory risk management processes.
Requirements
- Proficiency in programming using C++ and Python.
- Foundational understanding of derivatives pricing, risk, and exposure calculation concepts.
- Strong interest and foundational knowledge in Equity derivatives pricing, including concepts like stochastic volatility models, variance swaps, and basic exotic structures.
- Familiarity with Counterparty Credit Risk (CCR) calculations, including Basel IMM, Potential Future Exposure (PFE), and CVA methodologies is a significant advantage.
- Good understanding of probability theory and stochastic calculus.
- Familiarity with Numerical Analysis and Monte-Carlo methods.
- Experience developing software, preferably in Windows or Linux environments.
Responsibilities
- Contributing to the development and maintenance of in-house C++ and Python model libraries.
- Assisting in advancing the quantitative toolbox by exploring new technologies, algorithms, and numerical techniques.
- Participating in general efficiency improvement and optimization efforts within the analytical libraries.
- Collaborating with IT teams to integrate analytic libraries.
- Supporting the development and maintenance of critical quant infrastructure, databases, and productivity tools.
- Assisting in the build, testing, and release management of the model libraries.
- Contributing to Regulatory and Governance-based projects, particularly those related to Counterparty Credit Risk (CCR) such as Basel IMM, PFE, CVA, and RWA calculations, across a range of asset classes.
Other
- 1-2 years of relevant experience (post-bachelor's degree), ideally within a quantitative development or financial modeling role, or demonstrated strong academic achievement in a relevant field.
- Strong analytical and problem-solving skills.
- A meticulous and detailed approach, with a commitment to accuracy, is essential.
- Ability to take ownership of tasks and proactively follow up on issues.
- Demonstrated ability to work effectively in a team and to adapt to a fast-paced, high-pressure environment.
