Data Science Chief Expert, CX

SAP
Palo Alto
Workplace: HybridFull timeUSD 274,300 - 609,200 annuallyFunction: Data Science & Machine LearningExperience: 10+ yearsEducation: mastersSkills: ["Communication","Collaboration","Customer-facing","Agile collaboration","Analytical thinking"]

Build and scale SAP’s AI context engine for enterprise-ready agents by designing semantic foundations grounded in SAP’s business ontology. You’ll develop enterprise ontologies and semantic models, translate ambiguous business problems into AI use cases, and implement end-to-end machine learning and AI solutions from experimentation through production deployment and lifecycle support. Collaborate with product, engineering, business, and customers to deliver scalable, production-ready capabilities across SAP and non-SAP data landscapes.

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SAP
SAP
2 hours ago

Data Science Chief Expert, CX

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Job Summary

Build and scale SAP’s AI context engine for enterprise-ready agents by designing semantic foundations grounded in SAP’s business ontology. You’ll develop enterprise ontologies and semantic models, translate ambiguous business problems into AI use cases, and implement end-to-end machine learning and AI solutions from experimentation through production deployment and lifecycle support. Collaborate with product, engineering, business, and customers to deliver scalable, production-ready capabilities across SAP and non-SAP data landscapes.
Location: Palo Alto
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Build and scale a semantic and contextual layer that enables accurate enterprise AI agents grounded in SAP business master data and process semantics.
  • •Leverage SAP data models, metadata structures, and end-to-end process semantics to design and deliver AI and semantic data solutions across key business process areas.
  • •Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions, including deployment, production handoff, lifecycle support, and continuous improvement.
  • •Develop and maintain enterprise ontologies and semantic models to improve interoperability, entity consistency, and business context across SAP and non-SAP data landscapes.
  • •Translate ambiguous business challenges into concrete AI use cases and measurable outcomes, partnering with product, engineering, business, and customer-facing teams to ensure production readiness.
Travel: Low travel

Pay and Benefits

Salary: USD 274,300 - 609,200 annually

Key Requirements

  • •Master’s degree or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or related quantitative fields.
  • •10+ years of experience with machine learning, deep learning, statistical modeling, generative AI, and LLMs, including hands-on model development, evaluation, and improvement on real-world datasets.
  • •Strong Python and SQL skills, including production-grade Python development and experience with PyTorch, TensorFlow, and scikit-learn.
  • •Demonstrated experience deploying, shipping, and operating AI/ML solutions in production environments, including production handoff and lifecycle support.
  • •Experience designing and maintaining enterprise ontologies using OWL, RDF/RDFS, SKOS, and SHACL, with proficiency in SPARQL and graph query languages.
Experience:10+ yearsMachine learningDeep learningGenerative AILLMsKnowledge graphsSemantic data systems
Education:Master's in Computer Science, Applied Mathematics, Statistics, Engineering (or related quantitative fields)
Skills:CommunicationCollaborationCustomer-facingAgile collaborationAnalytical thinking
Tech Stack:PythonSQLPyTorchTensorFlowScikit-learnDatabricksSAP DatasphereSAP HANA Cloud Knowledge Graph EngineSAP Business Data CloudSAP One Domain ModelSAP Graph APISAP Business Accelerator HubAWSAzureGoogle Cloud PlatformOWLRDFRDFSSKOSSHACL

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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