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

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

Build and scale an AI context engine for SAP agents by leveraging enterprise business master data, process semantics, and knowledge graphs. Design and maintain enterprise ontologies/semantic models, translate business problems into measurable AI use cases, and develop end-to-end ML/AI solutions from experimentation through deployment and production support. Partner across product and engineering while using SAP data platforms and cloud infrastructure to deliver production-ready, trustworthy AI workflows.

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SAP
SAP
2 hours ago

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

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Job Summary

Build and scale an AI context engine for SAP agents by leveraging enterprise business master data, process semantics, and knowledge graphs. Design and maintain enterprise ontologies/semantic models, translate business problems into measurable AI use cases, and develop end-to-end ML/AI solutions from experimentation through deployment and production support. Partner across product and engineering while using SAP data platforms and cloud infrastructure to deliver production-ready, trustworthy AI workflows.
Location: Palo Alto
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Sr. Manager level

Key Responsibilities

  • •Leverage deep SAP data and process understanding to build AI and semantic data solutions using SAP master data domains and semantic infrastructure.
  • •Design and maintain enterprise ontologies/semantic models to improve interoperability and entity consistency across SAP and non-SAP data landscapes.
  • •Develop end-to-end ML/AI solutions for enterprise-scale problems, from preprocessing and feature engineering through evaluation, deployment, production handoff, and lifecycle support.
  • •Apply advanced ML/AI methods (including generative AI and LLM-based solutions) using enterprise data assets such as knowledge graphs and business process intelligence.
  • •Collaborate with product, engineering, business, and customer-facing teams to deliver scalable, practical, production-ready solutions and measurable business 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 a related quantitative field.
  • •10+ years of experience with machine learning, deep learning, statistical modeling, generative AI, and LLMs, including hands-on model development and improvement using real-world datasets.
  • •Strong Python and SQL skills, including 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 lifecycle support and continuous improvement.
  • •Experience with SAP and data/AI platforms and semantic technologies, including SAP Datasphere/HANA Cloud knowledge graph, SAP One Domain Model/Graph API, and ontology tooling (e.g., OWL/RDF/SHACL/SPARQL).
Experience:10+ years
Education:Master's
Skills:CommunicationCollaborationAnalytical thinkingCustomer-facing skillsAgile development
Tech Stack:PythonSQLPyTorchTensorFlowScikit-learnDatabricksSAP DatasphereSAP HANA CloudAWSAzureGoogle Cloud PlatformSAP Business Accelerator HubSAP One Domain ModelSAP Graph APISAP Business Data CloudSAP HANA Cloud Knowledge Graph EngineOrder-to-cashProcure-to-payRecord-to-reportPlan-to-produce

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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