Data Science Expert (Supply Chain Management) - Data Labs (m/f/d)
Core
Design and maintain enterprise ontologies and semantic models to ground SAP's AI agents in real business data and process context for supply chain domains.
Role type
Senior Applied Scientist (Semantic AI & Knowledge Engineering)
Builds
Unified semantic layers, RAG pipelines, embeddings, vector databases, and agentic AI solutions for supply chain planning and execution.
Domain
Enterprise Software / Supply Chain Management / Semantic AI
Deliverable
production ML models
Required skills
Knowledge engineering, semantic modeling, graph query languages (SPARQL/Cypher/GQL), GenAI systems (RAG/embeddings), Python, SQL, PyTorch/TensorFlow, cloud infrastructure (Databricks/AWS/Azure/GCP), production ML deployment
Preferred skills
SAP data models and business processes, W3C stack (OWL/RDF), supply chain domain expertise (demand/supply/logistics), time-series analysis and forecasting, agentic AI and reasoning frameworks
Technologies
SAP Datasphere, SAP HANA Cloud, SAP Knowledge Graph Engine, Databricks, AWS, Azure, GCP, PyTorch, TensorFlow, scikit-learn, SPARQL, Cypher, GQL
Responsibilities
Design and maintain enterprise ontologies and semantic models; Build AI capabilities including RAG pipelines and vector databases; Develop generative AI and LLM-based solutions using enterprise business data; 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
