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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 modes: 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
• Develop and implement analytics for counterparty credit risk management.
• Build infrastructure to consolidate counterparty credit risk models across systems.
• Perform quantitative research to implement model changes, enhancements and remediations.
• Work with stakeholders across business and functional teams during model development process.
• Create tools and dashboards which can enhance and improve the risk analysis.
• Conduct analysis on existing model short-comings and design remediation plans.
• Maintain, update and back-test risk models.
• Assess the methodologies and processes to identify potential weaknesses and the associated materiality of the risk
Qualifications
• At least a Master’s Degree in quantitative subject; PhD Degree is a plus.
• Deep understanding of pricing and risk calculations for financial derivatives.
• Strong analytical skills required to understand quantitative models, and to translate that understanding into sustainable library design, code development and integration into IT systems.
• 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
• Strong project management and organizational skills.
• Proficient programming skills in python (other languages such as R is a plus), and strong data handling skills in SQL.
• Excellent written skills (ability to produce well-structured model documentation).
• Excellent oral communication skills to be able to interact effectively with credit risk managers and other model users.
• Knowledge of Numerix and/or Bloomberg a plus.
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