Digital Asset Specialist

Data Strategy and Enablement • Lead the Data & AI Enablement agenda by defining and executing the data strategy aligned with the Group CDO and Digital Transformation plan. • Design and deliver the AI-enabled Data platform by establishing data pipelines and governance frameworks for AFF, Hertz, and related businesses. • Build AI capability by developing internal data science and ML delivery capabilities for use cases like credit risk, pricing, fraud detection, and collections optimization. Data Governance and Compliance • Implement policies, metadata management, lineage, and quality frameworks aligned with Group data leads. • Ensure data governance score achieves 95% with zero critical audit findings. Analytics and BI Delivery • Drive data analytics platform adoption, ensuring implementation of executive dashboards covering profitability, equity, RoE, and self-service analytics for business teams. • Aim for BI adoption rate of 80% with reduction in manual reports. Collaboration and Partnership Management • Collaborate with Group & Divisional teams to ensure synergy with AFS&TD, GTDP, EIB and initiatives to avoid duplication and ensure reuse of shared data assets. • Manage relationship with data engineering vendors, AI partners, and Group shared services (infrastructure, security) with SLA adherence of 95% and cost efficiency within budget. Required Skills To Be Successful: • Strong technical knowledge of Azure Data Factory, Power BI, SQL, and Fabric Lakehouse. • Familiarity with Python and ML frameworks such as Scikit-learn and Azure ML for model deployment. • Experience establishing and enforcing data governance towards certified data concepts, lineage, and quality frameworks. • Deep understanding of financial product data models, including Portfolio, Profitability, and RoE. • 10+ years in Data & Analytics roles with at least 5 years in leadership capacity. • Hands-on experience designing and delivering fully AI enabled data platforms. • Proven experience in AI/ML delivery, such as credit risk, pricing, and customer analytics, including building digital twins. • Track record of managing data engineering and BI delivery teams, both internal and vendor.