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The person filling the role would be expected to work on models across the department's remit, including CCAR finance regulatory models, as well as Treasury funding/liquidity models, RWA/capital models, stress-testing among other model types. The role may become more specialised over time but team members must be able to adapt to shifting workloads across areas
Engage with model owner and developers to ensure validation expectations around the supply of supporting materials required for validation are clear;
Perform technical analyses, data analyses, benchmarking, build challenger models (if needed) to support the validation review and challenge process for all new and existing models, to ensure accuracy of existing metrics to the standards required by the IHC IVU process and to drive continuous improvements in methodologies;
Produce high quality IHC IVU reports and presentations for relevant model governance committees, with a particular focus on noting limitations, weaknesses and assumptions
Support IVU management in their participation in different models committees, particularly the IHC Model Risk Committee and in conjunction with regulatory meetings
Stakeholder Management and Leadership
Contribute to ensuring that the IVU team provides high quality input and guidance to modellers across the bank to achieve consistency of standards and compliance with internal and external requirements;
Ensure open, transparent, proactive and timely interaction with major stakeholders (subject matter experts, model owners/developers) in alignment with Barclays Values and Behaviour principles
Ensure that the Group Model Risk Policy, IHC Model Risk Standards and other relevant requirements are upheld
Decision-making and Problem Solving
Self-study of developments in modelling and validation techniques
Attendance and contribution to internal technical presentations
3+ years experience in a quantitative role within risk management (credit/market/ operational), finance and/or project management in a financial institution
Highly numerate, as demonstrated by Honours degree, Masters or PhD (or similar) in a numerate subject such as Statistics, Economics, Mathematics, Physics, Operational Research, or Financial Engineering, or a track record of performance that demonstrates this ability.
Significant experience with Excel and other data management and computational tools
Able to produce high quality written communication including reviews of models, risk policies, and presentations for technical and non-technical audiences
Ability to manipulate large datasets
Experience in data quality and system testing
Familiarity with CCAR requirements, including governance and documentation standards.
Beyond risk management, knowledge in financial projection, capital management and treasury are highly desirable.
Ability to work within a large matrixed organization with competing requirements