Principal Data and Applied Scientist, SCM Autonomous Suite, Bellevue

SAP
Bellevue
Workplace: HybridFull timeUSD 193,400 - 420,200 annuallyFunction: Research & Scientific (R&D)Education: mastersSkills: ["Communication","Stakeholder management","Cross-functional collaboration"]

Build SAP’s AI context engine for autonomous supply-chain capabilities by designing enterprise ontologies and semantic models grounded in SAP business master data and process semantics. Develop production-ready GenAI and LLM-based capabilities, including RAG pipelines, embeddings, vector databases, and knowledge grounding. Apply machine learning, deep learning, and statistical modeling on real-world enterprise datasets, partnering across teams to deploy and continuously improve reliable AI workflows on modern cloud and data platforms.

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SAP
SAP
2 hours ago

Principal Data and Applied Scientist, SCM Autonomous Suite, Bellevue

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Last checked: 2 hours agoStatus: Live

Job Summary

Build SAP’s AI context engine for autonomous supply-chain capabilities by designing enterprise ontologies and semantic models grounded in SAP business master data and process semantics. Develop production-ready GenAI and LLM-based capabilities, including RAG pipelines, embeddings, vector databases, and knowledge grounding. Apply machine learning, deep learning, and statistical modeling on real-world enterprise datasets, partnering across teams to deploy and continuously improve reliable AI workflows on modern cloud and data platforms.
Location: Bellevue
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 ground AI agents in accurate understanding of SAP and connected business landscapes.
  • •Build and scale AI capabilities including RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding for production accuracy and reliability.
  • •Develop GenAI/LLM-based solutions using enterprise business data, knowledge graphs, business process intelligence, and structured/unstructured data assets.
  • •Apply machine learning, deep learning, and statistical modeling to develop, evaluate, and improve AI solutions using real-world enterprise datasets.
  • •Collaborate across product, engineering, business, and customer-facing teams to translate business challenges into deployed AI solutions and continuous improvements.
Travel: Low travel

Pay and Benefits

Salary: USD 193,400 - 420,200 annually

Key Requirements

  • •8+ 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 graph query language proficiency (SPARQL, Cypher, or GQL) and trade-offs between RDF triple stores and property graph databases.
  • •Hands-on experience with modern 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 such as PyTorch, TensorFlow, or scikit-learn.
Education:Master's
Skills:CommunicationStakeholder managementCross-functional collaboration
Tech Stack:PythonSQLPyTorchTensorFlowScikit-learnRAGEmbeddingsVector databasesLLMsMachine learningDeep learningSPARQLCypherGQLRDFRDFSOWLSKOSSHACLDatabricks

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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