Senior Data and Applied Scientist, Finance and Spend Autonomous Suite, Palo Alto

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

Build and scale SAP’s context engine for AI agents used in Finance and Spend. You will design enterprise ontologies and semantic models, harmonize knowledge across SAP and connected enterprise systems, and develop production-ready GenAI/RAG capabilities using vector databases and semantic retrieval. Partner across product, engineering, and customer-facing teams to turn business challenges into deployable AI/ML solutions grounded in SAP data and process semantics.

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FursaFursa
SAP
SAP
2 hours ago

Senior Data and Applied Scientist, Finance and Spend Autonomous Suite, Palo Alto

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

Job Summary

Build and scale SAP’s context engine for AI agents used in Finance and Spend. You will design enterprise ontologies and semantic models, harmonize knowledge across SAP and connected enterprise systems, and develop production-ready GenAI/RAG capabilities using vector databases and semantic retrieval. Partner across product, engineering, and customer-facing teams to turn business challenges into deployable AI/ML solutions grounded in SAP data and process semantics.
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 agent understanding of enterprise business data and process context.
  • •Build GenAI capabilities such as RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding for reliable production performance.
  • •Develop 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 and evaluate AI solutions on real-world enterprise datasets.
  • •Collaborate across product, engineering, business, and customer-facing teams to translate business challenges into deployable AI solutions and continuously improve them.
Travel: Low travel

Pay and Benefits

Salary: USD 148,600 - 306,300 annually

Key Requirements

  • •5+ years of experience in knowledge engineering, semantic data systems, applied AI, or data science.
  • •A Master's or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or a related quantitative field.
  • •Hands-on experience designing enterprise ontologies/semantic models and proficiency in at least one graph query language (SPARQL, Cypher, or GQL).
  • •Hands-on experience with GenAI systems (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:Enterprise AIMachine learningDeep learningGenAIKnowledge graphsRAG
Education:Master's
Skills:CommunicationStakeholder managementCross-functional collaboration
Tech Stack:PythonSQLPyTorchTensorFlowScikit-learnSPARQLCypherGQLRDFRDFSOWLSKOSSHACLRAGEmbeddingsVector databasesGraph queryDatabricksSAP DatasphereSAP HANA Cloud

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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