An international investment bank is looking to hire a Vice President level candidate within it's Quantitative Exposure Management function. This individual will be tasked with establishing a quantitative measurement framework for counterparty credit risk exposure, and conduct various types of modeling including but not limited to stress testing, VaR modelling, portfolio risk analysis, counterparty risk analytics and scenario analysis. This is a high exposure role, located in New York City.
What You Will Be Doing:
Working on establishing and developing the Quantitative Exposure Management framework
Developing analytics to measure counterparty credit risk for limits, capital and analysis
Developing methodologies and analytics related to haricuts/Independent-Amounts/Initial Margin
Overseeing the performance of the regulatory required SIMM model
A Successful Candidate Will Have:
At least 5 years of experience in quantitative counterparty credit risk management
Extensive knowledge of OTC derivatives, listed derivatives, and financial product expertise
Strong Quantitative skills in at least Python
At least a Masters Degree in a quantitative discipline (financial engineering, financial mathematics, mathematics, statistics etc.)
Knowledge of regulatory requirements for large financial institutions