| As part of the Group Risk Management team, the Associate Director, Counterparty Credit Risk Analytics is responsible for the conceptual design, development, and ongoing maintenance of the mathematical models used for the measurement and capitalization of the counterparty credit risk. This includes ensuring that the model’s underlying methodologies are appropriate and that they are implemented with integrity, to facilitate the effective management
Detailed responsibilities of the role include:
- Work with model users to understand their business requirements.
- Conduct research, review regulatory requirements and consult with industry stakeholders to evaluate best practices for modeling.
- Make recommendations on model methodologies, and develop technical implementation, either for production usage or to serve as a prototype for benchmark testing.
- Provide business requirements with technical implementation details and user acceptance criteria to technology teams for production deployment and validate implementation using independently developed benchmark models.
- Document model methodologies, implementation details and testing results, and work with internal validation to facilitate their approval of the models.
- Develop tools to assess and monitor model performance, including assumptions and limitations, on an ongoing basis for reporting to the various model monitoring governance committees.
- Investigate and remediate modeling issues identified through ongoing monitoring or by internal validation.
- Recalibrate models on a regular basis.
- Re-assessment and testing of models, including assumptions and limitations and benchmarking against alternative models, and documentation of the results in models’ whitepapers and annual assessments for review by internal validation.
Must-have Skills/Experiences and/or Education, certifications, qualifications, designations:
- Broad knowledge traded products across various asset classes and knowledge of regulatory & internal risk management requirements for CCR risk.
- Masters in Financial Engineering, or a degree in another quantitative subject such as physics, statistics, mathematics or mathematical finance and/or a relevant professional qualification, with concentration in quantitative methods and/or finance.
- Strong analytical and problem solving skills
- Excellent programming skills (e.g., Python, C++)
- Strong data management and analysis skills (SQL and Excel required).
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Nice-to-have Skills/Experience and/or Education, certifications, qualifications, designations:
- Financial Risk Manager certificate and/or Chartered Financial Analyst certificate.
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- Ability to work collaboratively to achieve team goals
- Agility to adapt to changing circumstances in a dynamic environment
Languages:
- Strong English communication skills, both written and verbal, especially in the explanation of complex modeling concepts to senior management and regulators
A hybrid work arrangement |
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