Senior Data & Applied Scientist - Ontologies & Semantics

SAP
Palo Alto
Workplace: HybridFull timeUSD 148,600 - 306,300 annuallyFunction: Research & Scientific (R&D)Experience: 5+ yearsSkills: ["Communication","Stakeholder management","Cross-functional collaboration","Agile collaboration","Ownership mindset"]

Build and scale a semantic context engine that powers accurate SAP AI agents and assistants. Design and maintain enterprise ontologies and semantic models, harmonizing SAP and external data into unified semantic layers. Develop production-ready GenAI/LLM capabilities using RAG, embeddings, vector databases, knowledge graphs, and business process intelligence, collaborating across product and engineering to deploy and continuously improve AI/ML solutions at enterprise scale.

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SAP
SAP
2 hours ago

Senior Data & Applied Scientist - Ontologies & Semantics

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Last checked: 2 hours agoStatus: Live

Job Summary

Build and scale a semantic context engine that powers accurate SAP AI agents and assistants. Design and maintain enterprise ontologies and semantic models, harmonizing SAP and external data into unified semantic layers. Develop production-ready GenAI/LLM capabilities using RAG, embeddings, vector databases, knowledge graphs, and business process intelligence, collaborating across product and engineering to deploy and continuously improve AI/ML solutions at enterprise scale.
Location: Palo Alto
Workplace: Hybrid
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Mid level

Key Responsibilities

  • •Design and maintain enterprise ontologies and semantic models that provide accurate, grounded understanding for SAP AI agents.
  • •Build and scale RAG pipelines and enterprise knowledge grounding using embeddings and vector databases for reliable production performance.
  • •Develop generative AI and LLM-based solutions using enterprise business data, knowledge graphs, business process intelligence, and other structured/unstructured assets.
  • •Leverage SAP data models, metadata structures, and process semantics across Order-to-Cash, Procure-to-Pay, Record-to-Report, and Plan-to-Produce to ground AI solutions.
  • •Partner across product, engineering, business, and customer-facing teams to translate business challenges into deployable AI solutions and continuously improve them.
Travel: Low travel

Pay and Benefits

Salary: USD 148,600 - 306,300 annually

Key Requirements

  • •5+ years of experience in knowledge engineering, semantic data systems, applied AI, or data science.
  • •Master’s or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or a related quantitative field.
  • •Hands-on experience designing enterprise ontologies and semantic models, including proficiency in graph query languages (SPARQL, Cypher, or GQL) and understanding RDF vs property graph trade-offs.
  • •Hands-on experience with GenAI systems such as RAG, embeddings, vector databases, semantic retrieval, and enterprise knowledge grounding.
  • •Strong Python and SQL skills with production-grade development practices, including experience with ML libraries (PyTorch, TensorFlow, or scikit-learn) and deploying AI/ML solutions in production.
Experience:5+ years
Education:
Skills:CommunicationStakeholder managementCross-functional collaborationAgile collaborationOwnership mindset
Tech Stack:PythonSQLRAGEmbeddingsVector databasesLLMsKnowledge graphsBusiness process intelligenceGraph query languagesSPARQLCypherGQLRDFRDFSOWLSKOSSHACLRDF triple storesProperty graph databasesPyTorch

Company Brief

SAP
Global enterprise software company best known for ERP systems and business applications covering finance, supply chain, procurement, HR, analytics, and customer management for large organizations.
Industry: Enterprise Software
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Walldorf, Germany
Founded: 1972
Glassdoor
Glassdoor: 4.1
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