Data exploration and validation: Stay close to the data through targeted hands-on exploration and validation, building a firsthand understanding of its characteristics, quality and suitability for model development. Relational enterprise data: Strong understanding of relational data, schemas, business entities and data quality challenges in enterprise environments. Skills used in this role: Model training, deep learning, feature engineering, ethical AI, data engineering, agentic orchestration, semantic retrieval, AI-assisted development, context engineering, AI output quality assurance, agentic AI day-to-day practice, AI-Assisted Automation and Prototyping, AI Adoption Capability. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, a
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