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The Model Validation - Quantitative Analyst is a key member of the Model Risk Management team, within the Group Risk Management and Assurance unit (CRO) and is responsible to perform independent technical validations on non-financial (e.g. Compliance, Machine Learning/Artificial Intelligence / generative AI) as well as financial (e.g. Stress Testing, Liquidity/ALM, Credit Risk, Market Risk, Investment/Research) models, enforcing model governance and validation standards, managing and reporting model risk to senior management.
YOUR CHALLENGE
- Perform independent validation of models (with a focus on AI and generative AI / Agentic AI / RAG systems) through statistical techniques, development of benchmark models and data analysis, in accordance with a multi-annual review plan. This includes:
- testing of the model’s assumptions, conceptual soundness, implementation, appropriateness of input data, model parameters, and their calibration accuracy
- performance of model risk rating assessments
- identification and evaluation of model limitations, and assessment of overall model risk in new and existing models
- production and delivery of model validation reports in high standards to evidence a sound challenge and risk-oriented validation findings
- Track and verify model risk mitigation activities and ensure adequate oversight over models through their lifecycle
- Maintain and further develop the model governance framework and model risk management processes
- Monitor model performance indicators along standardized risk metrics
- Build strong relationships and interact with model owners, developers, users, subject matter experts and Risk Management functions both at headquarter in Zurich and in foreign locations
YOUR PROFILE
- Higher university degree in a quantitative area (Artificial Intelligence, Mathematics, Engineering, Quantitative Finance), Master or PhD level, FRM or PRM is an advantage
- Profound knowledge and preferably a minimum of 2 years of experience working with non-financial models (e.g. Machine Learning, Artificial Intelligence, generative AI / agentic AI).
- Experience with financial models (e.g. Liquidity/ALM, Stress Testing, IRRBB, Market Risk, Credit Risk, Investment/Research/ESG) would be an advantage.
- Programming experience in languages such as Python, R, SQL.
- Autonomous working style, with the ability to demonstrate initiative defining validation scope, designing independent technical tests, clearing and reporting of validation outcome.
- Results-oriented individual with outstanding interpersonal skills, excellent written and verbal communication skills in English (German is an advantage).
- Focused on clients and can communicate impactfully with business partners, explaining technical and complex topics to a diverse audience.
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