Lead Data & AI Scientist, Enterprise Semantics
SAP
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Job summary
SAP is seeking a data and applied scientist to build the context engine for AI in finance and spend. You will design enterprise ontologies and semantic models, develop RAG pipelines, embeddings, and grounding using SAP data.
Work with Databricks, SAP Datasphere, and major cloud platforms to deploy reliable AI solutions. You will collaborate across product and engineering to translate complex business challenges into concrete AI solutions from concept to production, impacting enterprise-scale
Qualifications
- 8+ years in knowledge engineering or related AI/data science.
- Master's or PhD in CS, math, statistics, engineering, or related field.
- Design enterprise ontologies; proficient in graph query languages.
- GenAI systems experience: RAG, embeddings, vector databases.
- Strong Python and SQL with ML libraries; production experience.
- Big data infra and cloud (Databricks, AWS/Azure/GCP).
- Excellent communication and stakeholder management.
Responsibilities
- Design and maintain enterprise ontologies and semantic models.
- Build AI capabilities: RAG pipelines, embeddings, vector databases.
- Develop generative AI and LLM-based solutions with enterprise data.
- Ground AI solutions in SAP data models and business semantics.
- Collaborate with cloud platforms to support scalable AI workflows.
- Partner with product, engineering and business teams end-to-end.
- Apply ML and statistical modeling to real-world enterprise datasets.
Skills
Education
Tools
Job description
SAP is seeking a data and applied scientist to build the context engine for AI in finance and spend. You will design enterprise ontologies and semantic models, develop RAG pipelines, embeddings, and grounding using SAP data.
Work with Databricks, SAP Datasphere, and major cloud platforms to deploy reliable AI solutions. You will collaborate across product and engineering to translate complex business challenges into concrete AI solutions from concept to production, impacting enterprise-scale
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