Data Science Expert (Domain Models) - Data Labs (m/f/d)

SAP
Germany
Workplace: HybridFull timeFunction: Data Science & Machine LearningExperience: 8+ yearsSkills: ["Communication","Stakeholder management","Cross-functional collaboration"]

Build and scale SAP’s context engine for AI agents by designing enterprise ontologies and semantic models grounded in SAP business master data and process semantics. Develop production AI capabilities such as RAG pipelines, embeddings, vector databases, knowledge grounding, and LLM-based solutions using enterprise knowledge graphs and process intelligence. Partner across product, engineering, and customer-facing teams while deploying and operating AI/ML solutions in production across SAP and major cloud platforms.

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SAP
SAP
2 hours ago

Data Science Expert (Domain Models) - Data Labs (m/f/d)

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Last checked: 2 hours agoStatus: Live

Job Summary

Build and scale SAP’s context engine for AI agents by designing enterprise ontologies and semantic models grounded in SAP business master data and process semantics. Develop production AI capabilities such as RAG pipelines, embeddings, vector databases, knowledge grounding, and LLM-based solutions using enterprise knowledge graphs and process intelligence. Partner across product, engineering, and customer-facing teams while deploying and operating AI/ML solutions in production across SAP and major cloud platforms.
Location: Germany
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design and maintain enterprise ontologies and semantic models that enable AI agents to understand SAP and connected business landscapes.
  • •Integrate and harmonize data from SAP, Salesforce, Workday, ServiceNow, MES/IoT systems, and external providers into unified semantic layers.
  • •Build and scale AI capabilities including RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding for production reliability.
  • •Develop generative AI and 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, deploy, and continuously improve AI/ML solutions.
Travel: Low travel

Key Requirements

  • •8+ years of experience in knowledge engineering, semantic data systems, applied AI, or data science in industry, research labs, or advanced academic environments.
  • •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 trade-offs between RDF triple stores and property graph databases.
  • •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 with ML libraries such as PyTorch, TensorFlow, or scikit-learn.
Experience:8+ years
Education:
Skills:CommunicationStakeholder managementCross-functional collaboration
Tech Stack:PythonSQLPyTorchTensorFlowScikit-learnRAGEmbeddingsVector databasesSemantic retrievalKnowledge groundingLLMsGraph query languageSPARQLCypherGQLRDFRDFSOWLSKOSSHACL

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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