Senior Data and Applied Scientist, SCM Autonomous Suite, Palo Alto (Palo Alto, CA, US, 94304)

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

Build and scale SAP’s semantic and contextual foundation for enterprise AI agents, enabling accurate understanding of business master data, process flows, and domain relationships. Design and maintain ontologies and semantic models, and develop production-ready GenAI capabilities such as RAG pipelines, embeddings, vector databases, and knowledge grounding. Apply ML/deep learning to real-world enterprise datasets while partnering across product, engineering, and customer-facing teams to deploy and continuously improve AI solutions in the supply-chain domain.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
SAP
SAP
2 hours ago

Senior Data and Applied Scientist, SCM Autonomous Suite, Palo Alto (Palo Alto, CA, US, 94304)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Build and scale SAP’s semantic and contextual foundation for enterprise AI agents, enabling accurate understanding of business master data, process flows, and domain relationships. Design and maintain ontologies and semantic models, and develop production-ready GenAI capabilities such as RAG pipelines, embeddings, vector databases, and knowledge grounding. Apply ML/deep learning to real-world enterprise datasets while partnering across product, engineering, and customer-facing teams to deploy and continuously improve AI solutions in the supply-chain domain.
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 enable accurate AI understanding of SAP and connected business landscapes.
  • •Build and scale AI capabilities such as RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding for production accuracy and reliability.
  • •Develop GenAI and LLM-based solutions using enterprise business data, knowledge graphs, and business process intelligence.
  • •Use SAP data models, metadata structures, and business process semantics across Order-to-Cash, Procure-to-Pay, Record-to-Report, and Plan-to-Produce to ground AI solutions in real enterprise context.
  • •Apply machine learning, deep learning, and statistical modeling to develop, evaluate, and improve AI solutions using real-world enterprise datasets.
Travel: Low travel

Pay and Benefits

Salary: USD 148,600 - 306,300 annually

Key Requirements

  • •5+ years’ experience in knowledge engineering, semantic data systems, applied AI, or data science in industry, research labs, or advanced academics.
  • •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 at least one graph query language (SPARQL, Cypher, or GQL).
  • •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 and experience deploying AI/ML solutions in production.
Experience:5+ yearsKnowledge engineeringSemantic data systemsApplied AIData scienceResearch labsGenAIRAGSupply-chain
Education:Master's
Skills:CommunicationStakeholder managementCross-functional collaboration
Tech Stack:PythonSQLSPARQLCypherGQLRDFRDFSOWLSKOSSHACLRDF triple storesProperty graph databasesGenAILLMRAGEmbeddingsVector databasesSemantic retrievalKnowledge groundingKnowledge graphs

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
WebsiteLinkedInGlassdoor