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Embark on a transformative journey as an AIML Fraud and Compliance IVU at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionize our digital offerings, ensuring unapparelled customer experiences. Model Risk Management (MRM) reports directly to the Group Chief Risk Officer and responsible for the identification, assessment, monitoring and management of model risk within Barclays. Model risk is the potential for adverse consequences from decisions based on incorrect or misused model outputs. The Model Risk Management function’s mandate is to independently and actively manage model risk globally in line with the bank’s risk appetite.
Job Responsibility:
Validation of models for their intended use and scope, commensurate with the complexity and materiality of the models
Approval or rejection of a model or usage based on assessment of the model’s conceptual soundness, performance under intended use and the clarity of the documentation of the model’s inherent risks, limitations and weaknesses
Assessment of any compensating controls used to mitigate Model risk
Documentation of validation findings and recommendations in clear and concise reports, providing actionable insights for model improvement
Evaluation of the coherence of model interactions and quality of Large Model Framework aggregate results that generate output for regulatory submissions or management decision making and planning
Design of the framework and methodology to measure and, where possible, quantify model risk, including the assessment of framework level uncertainty
Requirements:
Experience in Risk or other parts of Investment Banks: ability to understand Risk and/or banking products and explain them at a high level
Experience in Model Monitoring: Understanding of the approach used for Model development, monitoring, model validation (regulatory capital models preferred)
Communication - Strong communication skills. Can produce concise, organized and thoughtful presentations for technical and non-technical audiences
Project Management – Ability to run projects independently and has a grasp of PM concepts and best practices
Experience of or exposure to Data Science: Ability to understand, discuss, design and challenge the approach
Nice to have:
Preferred qualifications – MBA, CA, Masters in Statistics, Finance or Engineering
Experience with Data Analysis tools (SAS, Python) and MS Suite (Word, Excel, PPT, Project, Visio and SharePoint skills)