Data Science Chief Expert, Domain Models

SAP
Palo Alto
Workplace: HybridFull timeUSD 274,300 - 609,200 annuallyFunction: Data Science & Machine LearningExperience: 10+ yearsEducation: phdSkills: ["Communication","Collaboration","Customer-facing skills","Analytical thinking","Cross-functional stakeholder management"]

Build SAP’s enterprise AI context engine by designing and scaling semantic and contextual foundations grounded in SAP business ontology. Leverage SAP master data, process semantics, and ontology/modeling approaches to create AI-ready knowledge layers. Develop and operationalize end-to-end ML/AI solutions, including generative AI and LLM-based systems, and deploy them in production with cloud and data platforms such as Databricks, SAP Datasphere, SAP HANA Cloud, AWS, Azure, or GCP.

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FursaFursa
SAP
SAP
2 hours ago

Data Science Chief Expert, Domain Models

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Job Summary

Build SAP’s enterprise AI context engine by designing and scaling semantic and contextual foundations grounded in SAP business ontology. Leverage SAP master data, process semantics, and ontology/modeling approaches to create AI-ready knowledge layers. Develop and operationalize end-to-end ML/AI solutions, including generative AI and LLM-based systems, and deploy them in production with cloud and data platforms such as Databricks, SAP Datasphere, SAP HANA Cloud, AWS, Azure, or GCP.
Location: Palo Alto
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Design and scale SAP’s semantic and contextual foundation that powers AI agents and assistants grounded in business master data and domain relationships.
  • •Leverage SAP data models, metadata structures, and process semantics across Order-to-Cash, Procure-to-Pay, Record-to-Report, and Plan-to-Produce to build AI and semantic data solutions.
  • •Design and maintain enterprise ontologies and semantic models to improve interoperability and entity consistency across SAP and non-SAP data landscapes.
  • •Develop, evaluate, and operationalize end-to-end machine learning and AI solutions from preprocessing and feature engineering through deployment, production handoff, and continuous improvement.
  • •Partner with product, engineering, business, and customer-facing teams to translate ambiguous business challenges into concrete AI use cases and measurable outcomes.
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 developing, evaluating, and improving models on real-world datasets.
  • •Strong production Python and SQL skills, with hands-on experience using ML libraries such as PyTorch, TensorFlow, and scikit-learn.
  • •Experience deploying and operating AI/ML solutions in production, including data preprocessing, feature engineering, experimentation, validation, and lifecycle support.
  • •Deep working knowledge of SAP data models, metadata structures, and core business processes, including SAP master data domains and Master Data Governance constructs.
Experience:10+ years
Education:PhD / Doctorate
Skills:CommunicationCollaborationCustomer-facing skillsAnalytical thinkingCross-functional stakeholder management
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
Glassdoor
Glassdoor: 4.1
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