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Job Description
Risk Analytics - Counterparty Credit Risk Quantitative Analyst
Quantitative specialist for developing and managing analytics for counterparty credit risk models. Candidate will join the Risk Analytics group that partakes in model development over the full life-cycle of models: from methodology to design to local implementation and validation. The successful candidate will also provide quantitative risk analysis to support daily counterparty credit risk management.
Responsibilities
1. Develop and implement analytics for counterparty credit risk management.
2. Build infrastructure to consolidate counterparty credit risk models across systems.
3. Perform quantitative research to implement model changes, enhancements and remediations.
4. Work with stakeholders across business and functional teams during model development process.
5. Create tools and dashboards which can enhance and improve the risk analysis.
6. Conduct analysis on existing model short-comings and design remediation plans.
7. Maintain, update and back-test risk models.
8. Assess the methodologies and processes to identify potential weaknesses and the associated materiality of the risk.
Qualifications
1. At least a Master's Degree in quantitative subject; PhD Degree is a plus.
2. Deep understanding of pricing and risk calculations for financial derivatives.
3. Strong analytical skills required to understand quantitative models, and to translate that understanding into sustainable library design, code development and integration into IT systems.
4. At least 3-5 years of experience in counterparty credit risk modeling, in particular experience working with credit simulation engines/models in a CRR and/or an XVA context.
5. Strong project management and organizational skills.
6. Proficient programming skills in python (other languages such as R is a plus), and strong data handling skills in SQL.
7. Excellent written skills (ability to produce well-structured model documentation).
8. Excellent oral communication skills to be able to interact effectively with credit risk managers and other model users.
9. Knowledge of Numerix and/or Bloomberg a plus.
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