Credit Risk Data Analyst

2 days ago

Glasgow, Glasgow City, United Kingdom Barclays Full time
About the Role

We are seeking a highly skilled Counterparty Risk Models Group (RMG) AVP to join our team at Barclays. As a key member of our Counterparty Credit Risk function, you will be responsible for acting as Model Owner for the bank's advanced Counterparty Credit Risk (CCR) exposure models.

Key Responsibilities
  • Model ownership throughout the model lifecycle, including CCR model monitoring, documentation, development, testing, validation, and remediation.
  • Contribute to a robust model governance framework by performing annual model reviews and quantitative analysis, model governance forum management, supporting audit activities, and assisting with regulatory exams and submissions.
  • Collaborate with technology to specify dependencies required for analytical solutions, such as data, development environments, and tools.
  • Implement analytics and models in accurate, stable, well-tested software and work with technology to operationalize them.
  • Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy.
  • Identify ways to mitigate risk and develop new policies/procedures in support of the control and governance agenda.
  • Take ownership for managing risk and strengthening controls in relation to the work done.
Requirements
  • Bachelor's degree in Maths, Statistics, Sciences, Accountancy, Finance, Business, Engineering, or Economics, or substantial directly related experience.
  • Keen interest in financial markets and Counterparty risk concepts.
  • Master's degree, or PhD in any of the aforementioned subjects.
  • Professional qualification such as CA/ACA/CFA/FRM.
  • Practical or academic knowledge in mathematical finance, statistics, and CCR exposure and capital metrics.
  • Advanced skills in Microsoft Office, including Excel. Experience with Python/SQL would be beneficial but not necessary.
Location

Glasgow

Purpose of the Role

To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making.

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