Data Science Chief Expert, Supply Chain Management

SAP
Bellevue, Washington
Workplace: HybridFull timeUSD 282,500 - 605,600 annuallyFunction: Data Science & Machine LearningExperience: 10+ yearsEducation: mastersSkills: ["Communication","Collaboration","Customer-facing skills","Analytical thinking","Cross-functional collaboration"]

Build AI that accurately understands enterprise business process semantics by creating and scaling a context engine grounded in SAP’s business ontology. Leverage SAP master data, metadata, and process flows to design semantic data solutions and enterprise ontologies. Develop and operationalize end-to-end ML/AI pipelines (including generative AI and LLMs), deploy production-ready workflows using cloud/data platforms, and partner with product, engineering, and business teams to deliver measurable outcomes.

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SAP
SAP
2 hours ago

Data Science Chief Expert, Supply Chain Management

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Job Summary

Build AI that accurately understands enterprise business process semantics by creating and scaling a context engine grounded in SAP’s business ontology. Leverage SAP master data, metadata, and process flows to design semantic data solutions and enterprise ontologies. Develop and operationalize end-to-end ML/AI pipelines (including generative AI and LLMs), deploy production-ready workflows using cloud/data platforms, and partner with product, engineering, and business teams to deliver measurable outcomes.
Location: Bellevue, Washington
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Develop and scale an enterprise AI context engine grounded in SAP’s business ontology, improving accuracy for SAP AI agents and assistants.
  • •Leverage SAP data models, metadata structures, and end-to-end business process semantics to build AI and semantic data solutions across major business process areas.
  • •Design and maintain enterprise ontologies/semantic models to improve interoperability, entity consistency, and business context across SAP and non-SAP systems.
  • •Translate ambiguous business challenges into concrete AI use cases, technical designs, and measurable business outcomes.
  • •Design, develop, evaluate, and operationalize end-to-end ML/AI solutions from data preprocessing through deployment, production handoff, lifecycle support, and continuous improvement.
Travel: Low travel

Pay and Benefits

Salary: USD 282,500 - 605,600 annually

Key Requirements

  • •Master’s degree or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or related quantitative fields.
  • •10+ years’ experience in machine learning, deep learning, statistical modeling, generative AI, and LLMs, including hands-on model development, evaluation, and improvement with real-world datasets.
  • •Strong Python and SQL skills with production-grade Python development and experience with ML libraries such as PyTorch, TensorFlow, and scikit-learn.
  • •Proven experience deploying and operating AI/ML solutions in production environments, including deployment handoff and lifecycle support.
  • •Deep working knowledge of SAP data models, metadata structures, core business processes, and SAP data/AI platform stack (e.g., SAP Datasphere, SAP HANA Cloud, SAP One Domain Model, SAP Graph API) plus enterprise ontology development with semantic technologies.
Experience:10+ yearsEnterprise AISemantic dataKnowledge graphsMachine learningGenerative AILLMsData platformsCloud
Education:Master's in Computer Science, Applied Mathematics, Statistics, Engineering, or related quantitative fields
Skills:CommunicationCollaborationCustomer-facing skillsAnalytical thinkingCross-functional collaboration
Tech Stack:PythonSQLPyTorchTensorFlowScikit-learnMachine learningDeep learningStatistical modelingGenerative AILLMsDatabricksSAP DatasphereSAP HANA CloudAWSAzureGoogle Cloud PlatformSAP Business Accelerator HubSAP One Domain ModelSAP Graph APISAP Business Data 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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