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Senior Quantitative Analyst

2 months ago

London, Greater London, United Kingdom ETRA Talent Full time
About the Role

We are seeking a highly skilled Senior Quantitative Analyst to join our team at ETRA Talent. As a Senior Quantitative Analyst, you will play a key role in the development and maintenance of statistical credit risk models that are integral to our global operations.

Key Responsibilities
  • Model Development: Deliver components of quantitative credit risk model development, including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) models.
  • Model Maintenance: Develop and maintain models under the Advanced Internal Ratings Based (AIRB) approach and IFRS9 provisioning process.
  • Data Quality and Analytics: Conduct data quality assessments and perform data analytics to support model development.
  • Challenger Model Development: Build and benchmark challenger models using advanced techniques, including machine learning.
  • Model Performance and Reporting: Assess model performance, impact, and reporting findings to senior management.
  • Collaboration and Stakeholder Engagement: Collaborate with risk transformation and data teams for model implementation and engage with stakeholders across global regions and disciplines to design best-in-class modelling approaches.
Requirements
  • Experience: Significant experience in wholesale credit risk modelling, including PD, EAD, and LGD models.
  • Knowledge: Excellent understanding of AIRB and/or IFRS9 credit risk modelling frameworks.
  • Regulatory Compliance: Familiarity with UK (PRA) or EU (EBA/ECB) regulatory requirements.
  • Technical Skills: Proficiency in manipulating large data sets, particularly using Python, and a strong grasp of credit risk-related data.
  • Communication Skills: Ability to communicate complex technical concepts to non-technical stakeholders.
  • Collaboration Skills: Proven track record of cross-functional collaboration in a global environment.
Desirable Skills
  • Programming Languages: Experience with Python, SAS, and SQL.
  • Model Implementation: Knowledge of model implementation within a banking environment, linked to policies and regulations.
  • Language Skills: Proficiency in English, both written and verbal.