Data Science Leader, Spend Management (Singapore, SG, 117440)

SAP
Singapore
Workplace: HybridFull timeFunction: Data Science & Machine LearningSkills: ["Leadership","Stakeholder management","Executive communication","Technical strategy","Mentoring"]

Lead SAP’s Data and Applied Science team to build and scale the semantic context engine that makes SAP AI agents accurate and grounded in enterprise business master data. Drive strategy, team priorities, and delivery of large-scale AI programs from concept to production across stakeholders. Partner with executives to define AI investment priorities and establish governance, platform capabilities, and knowledge-graph/ontology-driven enterprise intelligence.

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FursaFursa
SAP
SAP
2 hours ago

Data Science Leader, Spend Management (Singapore, SG, 117440)

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Job Summary

Lead SAP’s Data and Applied Science team to build and scale the semantic context engine that makes SAP AI agents accurate and grounded in enterprise business master data. Drive strategy, team priorities, and delivery of large-scale AI programs from concept to production across stakeholders. Partner with executives to define AI investment priorities and establish governance, platform capabilities, and knowledge-graph/ontology-driven enterprise intelligence.
Location: Singapore
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Sr. Manager level

Key Responsibilities

  • •Build and scale the semantic and contextual foundation powering SAP’s AI agents and assistants grounded in SAP’s Business ontology.
  • •Define and execute AI program strategy, priorities, and delivery across multiple teams and business units from concept to production.
  • •Establish model governance and responsible AI practices, plus operational frameworks for enterprise-scale deployments.
  • •Design and scale ontology-driven enterprise intelligence solutions, including knowledge graphs, semantic layers, and business knowledge models.
  • •Evaluate and apply emerging AI technologies, including MLOps/LLMOps and pragmatic build-versus-buy decisions across platform investments and roadmaps.
Travel: Low travel

Key Requirements

  • •10+ years leading, mentoring, and growing high-performing teams of data scientists/ML engineers/AI practitioners, delivering complex AI initiatives to production across multiple teams.
  • •Ability to define technical strategy, set team priorities, and align AI investments with business objectives, product roadmaps, and customer outcomes.
  • •Experience building a culture of technical excellence, operational rigor, and continuous learning.
  • •5+ years of people management experience leading data science and AI teams, including hiring, coaching, and retaining top AI talent.
  • •Knowledge of SAP’s domains, data models, metadata structures, and core business processes end-to-end.
Experience:AIMachine learningEnterprise AIKnowledge graphsSemantic technologiesEnterprise intelligence
Skills:LeadershipStakeholder managementExecutive communicationTechnical strategyMentoring
Tech Stack:SAP DatasphereSAP HANA Cloud Knowledge Graph EngineSAP Business Data CloudSAP One Domain ModelSAP Graph APISAP Business Accelerator HubAI/ML architectureModel governanceML OpsLLM OpsKnowledge graphsOntologiesSemantic technologiesRAGVector/keyword searchLakehouse architecturesEntity resolutionTaxonomyMetadata management

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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