Senior Data Scientist (Supply Chain Management) - Data Labs (m/w/d)
Core
Build the semantic and contextual foundation for SAP's AI agents by designing enterprise ontologies, RAG pipelines, and knowledge grounding systems that transform raw business data into accurate, grounded understanding for supply chain decision intelligence.
Role type
Senior Applied Scientist (Supply Chain & Semantic AI)
Builds
Supply-chain ontology packs, reusable semantic data products, forecasting and optimization models, and typed agent interfaces for SAP IBP, Joule, and Autonomous SCM agents.
Domain
Enterprise Software / Supply Chain Management / Knowledge Engineering / Generative AI
Deliverable
production ML models
Required skills
Knowledge engineering, semantic modeling, graph query languages (SPARQL/Cypher/GQL), RAG pipelines, embeddings, vector databases, Python, SQL, PyTorch/TensorFlow, cloud platforms (Databricks/AWS/Azure/GCP), production ML deployment
Preferred skills
SAP data models and business processes, W3C stack (OWL/RDF), supply chain domain expertise (planning/logistics), time-series analysis and forecasting, agentic AI and reasoning frameworks, mathematical optimization
Technologies
SAP Datasphere, SAP HANA Cloud Knowledge Graph Engine, SAP Business Data Cloud, SAP One Domain Model, SAP Graph API, Databricks, AWS, Azure, GCP, PyTorch, TensorFlow, scikit-learn, SPARQL, Cypher, GQL
Responsibilities
Design and maintain enterprise ontologies and semantic models for AI agents; Build AI capabilities including RAG pipelines and enterprise knowledge grounding; Develop generative AI and LLM-based solutions using business data; Leverage SAP data models and process semantics to ground AI solutions; Work with cloud and data platforms to support scalable AI workflows; Partner across teams to translate business challenges into AI solutions; Apply machine learning and statistical modeling to evaluate AI solutions.
Seniority
Senior, hands-on IC
