Senior Data and Applied Science - SAP Data Labs - CX Team (Bangalore, IN, 560066)

SAP
Bengaluru
Workplace: HybridFull timeFunction: Laboratory & Clinical OperationsExperience: 6+ yearsEducation: mastersSkills: ["Communication","Stakeholder management","Cross-functional collaboration"]

Build and scale the semantic and contextual “context engine” behind SAP’s AI agents, grounded in SAP’s business ontology and enterprise data. Design and maintain enterprise ontologies and semantic models, harmonize data across SAP and other systems into unified semantic layers, and develop production AI capabilities such as RAG, embeddings, vector databases, and LLM-based solutions. Apply ML and deep learning to real enterprise datasets and collaborate cross-functionally to deploy and continuously improve in production.

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SAP
SAP
2 hours ago

Senior Data and Applied Science - SAP Data Labs - CX Team (Bangalore, IN, 560066)

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Job Summary

Build and scale the semantic and contextual “context engine” behind SAP’s AI agents, grounded in SAP’s business ontology and enterprise data. Design and maintain enterprise ontologies and semantic models, harmonize data across SAP and other systems into unified semantic layers, and develop production AI capabilities such as RAG, embeddings, vector databases, and LLM-based solutions. Apply ML and deep learning to real enterprise datasets and collaborate cross-functionally to deploy and continuously improve in production.
Location: Bengaluru
Workplace: Hybrid
Employment Type: Full time
Job Function: Laboratory & Clinical Operations
Seniority: Mid level

Key Responsibilities

  • •Design and maintain enterprise ontologies and semantic models that give SAP’s AI agents accurate, grounded understanding of SAP and connected business landscapes.
  • •Build and scale AI capabilities including RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding for accurate, reliable production performance.
  • •Develop GenAI and LLM-based solutions using enterprise business data, knowledge graphs, business process intelligence, and structured/unstructured data assets.
  • •Leverage 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.
  • •Apply machine learning, deep learning, and statistical modeling to develop and evaluate AI solutions using real-world enterprise datasets, collaborating across teams from concept through continuous improvement.
Travel: Low travel

Key Requirements

  • •6+ 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; 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; experience with ML libraries such as PyTorch, TensorFlow, or scikit-learn.
Experience:6+ years
Education:Master's in Computer Science, Applied Mathematics, Statistics, Engineering, or a related quantitative field
Skills:CommunicationStakeholder managementCross-functional collaboration
Tech Stack:PythonSQLPyTorchTensorFlowScikit-learnSPARQLCypherGQLRDFRDFSOWLSKOSSHACLRAGEmbeddingsVector databasesDatabricksSAP DatasphereSAP HANA CloudAWS

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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