Data Science Chief Expert, SCM (Palo Alto, CA, US, 94304)

SAP
Palo Alto
Workplace: HybridFull timeUSD 274,300 - 609,200 annuallyFunction: Data Science & Machine LearningExperience: 10+ yearsEducation: phdSkills: ["Communication","Collaboration","Customer-facing skills","Agile development","Curiosity"]

Build and scale the AI context engine that turns SAP enterprise data and process semantics into trusted knowledge for SAP’s AI agents and assistants. Design semantic models and ontologies, harmonize SAP and non-SAP master data into unified layers, and develop end-to-end ML/AI solutions from preprocessing and feature engineering through production deployment and lifecycle support. Work across cloud data platforms and SAP’s data/graph/accelerator assets to deliver measurable outcomes.

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SAP
SAP
2 hours ago

Data Science Chief Expert, SCM (Palo Alto, CA, US, 94304)

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Job Summary

Build and scale the AI context engine that turns SAP enterprise data and process semantics into trusted knowledge for SAP’s AI agents and assistants. Design semantic models and ontologies, harmonize SAP and non-SAP master data into unified layers, and develop end-to-end ML/AI solutions from preprocessing and feature engineering through production deployment and lifecycle support. Work across cloud data platforms and SAP’s data/graph/accelerator assets to deliver measurable outcomes.
Location: Palo Alto
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Leverage SAP data and process understanding across order-to-cash, procure-to-pay, record-to-report, and plan-to-produce to build AI and semantic data solutions using SAP master data domains and modeling assets.
  • •Design 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 needs into concrete AI use cases, technical designs, and measurable business outcomes.
  • •Design, develop, evaluate, and operationalize end-to-end ML and AI solutions, including deployment, production handoff, lifecycle support, and continuous improvement.
  • •Partner with product, engineering, business, and customer-facing teams to ensure solutions are scalable, production-ready, and adopted in enterprise processes.
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 a related quantitative field.
  • •10+ years of experience with 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, including production-grade Python development and ML libraries such as PyTorch, TensorFlow, and scikit-learn.
  • •Proven experience deploying, shipping, and operating AI/ML solutions in production environments, including production handoff and lifecycle support.
  • •Hands-on knowledge of SAP data models, metadata structures, and core business processes, plus SAP platform stack components (e.g., SAP Datasphere, SAP HANA Cloud Knowledge Graph Engine, SAP Business Data Cloud, SAP One Domain Model, SAP Graph API, SAP Business Accelerator Hub).
Experience:10+ years
Education:PhD / Doctorate
Skills:CommunicationCollaborationCustomer-facing skillsAgile developmentCuriosity
Tech Stack:PythonSQLPyTorchTensorFlowScikit-learnDatabricksSAP DatasphereSAP HANA CloudAWSAzureGoogle Cloud PlatformSAP One Domain ModelSAP Graph APISAP Business Accelerator HubSAP Business Data CloudSAP HANA Cloud Knowledge Graph EngineOWLRDFRDFSSKOS

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
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Glassdoor: 4.1
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