Senior Data Scientist (Supply Chain Management) - Data Labs (m/f/d)
Core
Build the semantic and contextual foundation for SAP's AI agents by designing enterprise ontologies, RAG pipelines, and knowledge grounding systems that enable accurate understanding of complex supply chain business processes.
Role type
Senior Applied Data Scientist (Supply Chain & Semantic AI)
Builds
Semantic layers, AI agent capabilities, forecasting and optimization models for supply chain planning and execution.
Domain
Enterprise Software / Supply Chain Management / Generative AI / Knowledge Engineering
Deliverable
production ML models
Required skills
Knowledge engineering, semantic modeling, RAG pipelines, embeddings, vector databases, Python, SQL, PyTorch, TensorFlow, scikit-learn, cloud infrastructure (Databricks, AWS, Azure, GCP), production deployment of AI/ML solutions
Preferred skills
SAP data models and business processes, W3C stack (OWL, RDF/RDFS), supply chain domain expertise (demand planning, inventory, logistics), time-series analysis, causal inference, agentic AI architectures
Technologies
Databricks, SAP Datasphere, SAP HANA Cloud, AWS, Azure, GCP, SPARQL, Cypher, GQL, PyTorch, TensorFlow, scikit-learn
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 enterprise business data; Leverage SAP data models and business 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 concrete AI solutions; Apply machine learning and statistical modeling to evaluate AI solutions
Seniority
Senior, hands-on IC
