CAIA's Career Center is an easy-to-use, comprehensive resource connecting job seekers with employers in the growing AI field. Use your knowledge and credibility to advance your career or build a talented team for your organization. Opportunities targeted to CAIA Charterholders are prioritized.
In order to search for jobs specifically for CAIA Charterholders or those pursuing the CAIA Charter please enter “CAIA” in the search panel.
This will enable you to search for CAIA specific roles globally.
Counterparty Risk is the risk that a counterparty to the firm does not fulfill its contractual obligations in full, typically as a result of the default of the counterparty. The associated Counterparty Valuation Adjustment (CVA) is the fair value of the compensation required for taking on this risk. Our client is a pioneer and industry leader in counterparty risk measurement and management. Counterparty risk has become a key focus for the financial industry and regulators in the wake of the financial crisis.
The Quantitative Research Group for Counterparty Credit Risk is responsible for developing and supporting models to measure counterparty risk in the investment bank. The group is also responsible for the wider XVA modelling e.g. modeling funding valuation adjustments (FVA) as well as credit risk capital. Counterparty risk models are highly complex cross-asset class portfolio valuation models.
Design and implement new cutting-edge, cross-asset, counterparty risk simulation models as well as enhance the existing library.
Support the XVA trading desk and Credit risk organization in pricing and risk managing credit risk.
Work closely with asset aligned quantitative research groups in order to onboard new products into the counterparty risk valuation framework.
Liaise with technology teams in order to build out risk management systems and front end tools.
Ensure clear documentation and testing of models and work closely with the model review group in order to facilitate model approvals.
Liaise with Valuation Control and risk groups to understand limitations and risks in existing models and help in setting appropriate reserves and limits
Essential skills, experience, and qualifications:
PhD or MS degree in Math, Math Finance, Physics, Computer Science, Engineering or similar.
Deep understanding of probability theory, stochastic processes, PDEs, and numerical methods.
Excellent analytical and problem solving abilities.
Extensive C/C++ coding experience
Excellent communication skills (written and verbal).
Team work oriented.
Desirable skills, experience, and qualifications:
Experience in Counterparty Risk Modelling (CVA), funding valuation adjustment (FVA) or credit risk capital.