Location: United Kingdom (London, City of) Type: Permanent
Counterparty Credit Risk Quant – VP/ED level
The Counterparty Credit Risk team within the Quantitative Research group (QR CCR) is responsible for developing and supporting models to measure counterparty risk and funding costs for the investment bank. This requires large scale cross-asset scenario generation engines as well as highly optimized portfolio valuation models. The counterparty exposure calculations are used for credit exposure management, CVA & FVA hedging as well credit risk capital calculations. The responsibilities of the team span the full range of activities from new model specification, managing model approval, model implementation and support of our various stakeholders, including trading, risk, technology and capital reporting functions.
Design and implement new testing and diagnostic tools for identifying and understanding model weaknesses and their impacts. Tests include, among others, a variety of statistical tests, benchmarking against alternative models, testing calibration and implementation. Impact assessments can be risk-based or via comparison to alternative approaches, and often bespoke solutions will be required, tailored to the underlying model and its limitation.
Lead interpretation of test results and remediation work, including communications with stakeholders and coordination or direct implementation of modelling enhancements.
Working closely with asset-aligned Quantitative Research groups in order to understand and address product-level pricing limitations.
Liaising with technology teams in order to build out risk management systems and run diagnostics tools.
Ensuring clear documentation and testing of models and working closely with the Model Review Group in order to facilitate model approvals.
Supporting the trading team and risk organisation in pricing and risk managing credit risk and understanding of model limitations.
Liaising with Valuation Control and risk groups to understand limitations and risks in existing models and help in setting appropriate reserves and limits.
Required Skills and Experience:
A very structured mathematical approach to problem solving, experience with quantitative modeling, time series / econometrical analysis, hypothesis testing and general statistics, risk neutral pricing, business overview, and the ability to work in a dynamic environment.
Excellent communication skills are required in the interaction with trading, technology, and control functions. Ideally, you will also have a healthy interest in good software design principles.
A PhD. in a numerate subject from a top academic institution is a plus, but not an absolute requirement.
Very strong mathematical and financial modeling skills. Good knowledge of risk neutral pricing approaches for a variety of asset classes (e.g. interest rates, inflation, equity, FX). Good knowledge or understanding of statistical testing, times series analysis, econometrics.
Strong interest in programming and design. Ideally some experience with coding in Python. In addition, experience with C++ would be a plus.
Strong communication and documentation skills. Ability to present technical information clearly.
Pro-active attitude. Should have a natural interest to learn about our business, models, and infrastructure, and also desire and drive to identify, quantify, and fix model issues and limitations.