Exposure Management Data Analyst 100% (f/m/d)

At Julius Baer, we celebrate and value the individual qualities you bring, enabling you to be impactful, to be entrepreneurial, to be empowered, and to create value beyond wealth. Let’s shape the future of wealth management together.

• Own, maintain, and extend the dashboards and reports through which the bank sees its security exposure, covering a growing estate of modules. Immediate focus falls on the established practices: penetration testing, infrastructure vulnerabilities, and security configuration baseline compliance
• Devise, document, and version the formulas behind our exposure measures, so that every published figure has one definition, one calculation, and one owner
• Build and maintain the searches and transformations that aggregate per-asset security results at scale, including the coverage checks that distinguish an asset that passed from an asset that stopped reporting
• Define the measures for exposure domains being brought under management for the first time, where no established metric exists to inherit. You will propose the definition, defend it, and build the reporting behind it
• Design, validate, and support the adoption of an aggregated per-service exposure score intended to enable proportionate, risk-based governance. This begins as an experiment, and you will be responsible for establishing whether it earns operational use. Key partners will include stakeholders across delivery and governance functions
• Replace the manual compilation of responses to supervisory requests with a standardized, reusable, and reproducible reporting capability, including the mapping from each requirement to the underlying data

• Hands-on expertise with an enterprise business intelligence platform (Tableau preferred): data modelling, calculated fields, level-of-detail expressions, extract strategy, and performance tuning
• Proven ability to design and document metrics and composite scores, covering weighting, treatment of missing data, sensitivity, and validation
• Experience defining a measure from scratch in a domain that had none and getting it accepted by the people it measures
• Scripting for data transformation and automation, ideally in Python, with the discipline to produce maintainable, documented, version-controlled work
• Bachelor's degree in computer science, data engineering, information security, or equivalent practical experience
• Five or more years of experience in data analytics or data engineering, including direct responsibility for reporting that other people depend on
• Fluency in English

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