Senior Quantitative Risk Analyst

14 hours ago


London, Greater London, United Kingdom ETRA Talent Full time
Senior Quantitative Analyst, Credit Risk

ETRA Talent is seeking an experienced Senior Quantitative Analyst, Credit Risk to join our client's Model Development team in London. This role offers a unique opportunity to contribute to the development and maintenance of statistical credit risk models that are integral to our client's global operations.

Key Responsibilities:
  • Deliver components of quantitative credit risk model development, including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) models.
  • Conduct data quality assessments and perform data analytics to support model development.
  • Build and benchmark challenger models using advanced techniques, including machine learning.
  • Assess model performance, impact, and report findings to senior management.
  • Collaborate with risk transformation and data teams for model implementation.
Requirements:
  • Significant experience in wholesale credit risk modeling, including PD, EAD, and LGD models.
  • Excellent understanding of AIRB and/or IFRS9 credit risk modeling frameworks.
  • Familiarity with UK (PRA) or EU (EBA/ECB) regulatory requirements.
  • Proficiency in manipulating large data sets, particularly using Python, and a strong grasp of credit risk-related data.
  • Experience with Python, SAS, and SQL.
  • Knowledge of model implementation within a banking environment, linked to policies and regulations.
  • Proficiency in English, both written and verbal.
Quantitative Analyst, Credit Risk

ETRA Talent is seeking a Quantitative Analyst, Credit Risk to join our client's team in London. This role offers an excellent opportunity for professionals looking to further their career in credit risk analytics.

Key Responsibilities:
  • Conduct data quality assessments and analytics to support model development.
  • Work closely with team leads to ensure successful model implementation and stakeholder engagement.
  • Experience in credit risk modeling, particularly in PD, LGD, and EAD.
  • Familiarity with data manipulation tools, preferably Python.
  • Knowledge of Python, SAS, and SQL.
  • Understanding of regulatory requirements and model implementation processes.
Requirements:
  • Experience in credit risk modeling, particularly in PD, LGD, and EAD.
  • Familiarity with data manipulation tools, preferably Python.
  • Knowledge of Python, SAS, and SQL.
  • Understanding of regulatory requirements and model implementation processes.


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