Counterparty Credit Risk Analyst

Join our Counterparty Credit Risk team and help shape how we measure and manage risk across dynamic financial markets. You will enhance stress testing and scenario methodologies, develop analytical tools, and deliver insights that support strong risk decisions. This role combines quantitative problem-solving, data engineering, and close partnership with stakeholders across risk, technology, and the business. If you are curious, hands-on, and motivated by complex challenges, we would like to hear from you.

As a Counterparty Credit Risk Analyst in Counterparty Credit Risk Methodology and Stress Testing, you will design and enhance stress testing frameworks, build quantitative analytics, and automate risk processes to strengthen transparency, controls, and decision-making.

Design, enhance, and maintain counterparty credit risk stress testing methodologies, scenario frameworks, and supporting documentation Perform sensitivity analysis, backtesting, and scenario reviews to assess portfolio vulnerabilities and validate methodology performance Analyze counterparty exposures and concentration drivers using quantitative models, risk management frameworks, and relevant risk metrics Develop Python-based analytics and automation solutions that improve efficiency, control, and data quality across stress testing and monitoring workflows Improve risk monitoring transparency through explainable metrics, governance-ready reporting, and well-controlled processes Partner with stakeholders across Risk, Quantitative Research, Technology, Credit, and the business to deliver analytical insights and process enhancements Support delivery of practical artificial intelligence and large language model applications for risk monitoring, workflow automation, and management reporting Prepare regulator- and audit-ready materials, including methodology papers, testing evidence, and governance artifacts Required qualifications, capabilities, and skills Bachelor’s or Master’s degree in Mathematics, Statistics, Financial Engineering, Physics, Engineering, Finance, Economics, or a related quantitative discipline 3 years of experience in risk management, quantitative analytics, stress testing, or a related area within financial services Proficiency in Python and experience building analytics, automation, and data-driven solutions Understanding of financial markets and core risk management concepts Experience with stress testing, scenario analysis, quantitative risk methodologies, or model validation practices Experience creating clear, effective visualizations using tools such as Tableau or Power BI Knowledge of artificial intelligence and large language model concepts and practical applications in analytics or risk management Strong analytical and problem-solving skills with attention to detail and a control-minded approach Strong written and verbal communication skills, including the ability to explain complex topics to technical and non-technical audiences Ability to manage multiple priorities and deliver high-quality outputs in a fast-paced environment Preferred qualifications, capabilities, and skills Financial Risk Manager (FRM), Chartered Financial Analyst (CFA), or equivalent professional certification Experience in counterparty credit risk, including derivatives, futures and options, or securities financing transactions Experience working with large datasets and modern data platforms Experience with cloud platforms and scalable analytics tooling Experience writing methodology documentation and supporting audit, regulatory, or governance reviews Experience improving end-to-end processes through controls design and automation Advanced proficiency in Tableau or Power BI, including dashboard design and governance considerations