Data Science Expert

SAP
Bengaluru
Workplace: HybridFull timeFunction: Data Science & Machine LearningExperience: 10+ yearsEducation: mastersSkills: ["Communication","Stakeholder management","Cross-functional collaboration"]

Build SAP’s enterprise AI context engine for accurate, grounded AI agents. Design and maintain ontologies, semantic models, and unified semantic layers that harmonize enterprise data across SAP and connected systems. Develop production-grade AI capabilities such as RAG pipelines, embeddings, vector databases, knowledge graphs, and LLM-based solutions. Apply ML, deep learning, and statistical modeling, partner across teams for deployment, and work with cloud data platforms including Databricks and SAP HANA Cloud.

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FursaFursa
SAP
SAP
2 hours ago

Data Science Expert

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Job Summary

Build SAP’s enterprise AI context engine for accurate, grounded AI agents. Design and maintain ontologies, semantic models, and unified semantic layers that harmonize enterprise data across SAP and connected systems. Develop production-grade AI capabilities such as RAG pipelines, embeddings, vector databases, knowledge graphs, and LLM-based solutions. Apply ML, deep learning, and statistical modeling, partner across teams for deployment, and work with cloud data platforms including Databricks and SAP HANA Cloud.
Location: Bengaluru
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 ground SAP AI agents in enterprise business master data and process context.
  • •Build and scale unified semantic layers harmonizing data from SAP and connected systems into production-ready knowledge for AI agents.
  • •Develop and implement GenAI capabilities including RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding.
  • •Develop LLM-based solutions using enterprise business data, knowledge graphs, and structured/unstructured assets, leveraging business process semantics.
  • •Work with cloud and data platforms (Databricks, SAP Datasphere, SAP HANA Cloud, AWS, Azure, GCP) and partner across teams to deploy and continuously improve AI workflows.
Travel: Low travel

Key Requirements

  • •10+ 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 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:10+ yearsApplied AIKnowledge engineeringGenAIEnterprise AI
Education:Master's
Skills:CommunicationStakeholder managementCross-functional collaboration
Tech Stack:PythonSQLPyTorchTensorFlowScikit-learnRAGEmbeddingsVector databasesSPARQLCypherGQLRDFRDFSOWLSKOSSHACLDatabricksSAP 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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