Data Science Chief Expert, CX

SAP
Montreal
Workplace: HybridFull timeCAD 216,900 - 537,300 annuallyFunction: Data Science & Machine LearningExperience: 10+ yearsSkills: ["Communication","Collaboration","Customer-facing skills","Analytical thinking","Cross-functional collaboration"]

Build and scale the semantic context engine powering SAP’s AI agents and assistants. Leverage SAP master data domains, business process semantics, and enterprise ontologies to deliver accurate knowledge layers for AI, including generative/LLM solutions and knowledge graphs. Design and operationalize end-to-end ML/AI pipelines, work across cloud data platforms, and partner with product, engineering, and customer-facing teams to ensure production-ready, scalable AI capabilities.

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SAP
SAP
2 hours ago

Data Science Chief Expert, CX

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Last checked: 2 hours agoStatus: Live

Job Summary

Build and scale the semantic context engine powering SAP’s AI agents and assistants. Leverage SAP master data domains, business process semantics, and enterprise ontologies to deliver accurate knowledge layers for AI, including generative/LLM solutions and knowledge graphs. Design and operationalize end-to-end ML/AI pipelines, work across cloud data platforms, and partner with product, engineering, and customer-facing teams to ensure production-ready, scalable AI capabilities.
Location: Montreal
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Leverage deep SAP data and process understanding to build AI and semantic data solutions using SAP master data domains and process semantics.
  • •Design and maintain enterprise ontologies/semantic models to improve interoperability, entity consistency, and business context across SAP and non-SAP data landscapes.
  • •Develop and operationalize end-to-end machine learning and AI solutions, from data preprocessing and experimentation through deployment, handoff, and continuous improvement.
  • •Apply advanced AI methods (machine learning, deep learning, statistical modeling, data mining, optimization) to solve enterprise-scale problems using structured and unstructured enterprise data.
  • •Translate ambiguous business challenges into AI use cases and measurable outcomes, partnering with product, engineering, business, and customer-facing teams for production-ready scalability.
Travel: Low travel

Pay and Benefits

Salary: CAD 216,900 - 537,300 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 on real-world datasets.
  • •10+ years of experience across machine learning, data science, applied AI, AI research, knowledge engineering, or semantic data systems.
  • •Strong Python and SQL with production-grade development and ML libraries such as PyTorch, TensorFlow, and scikit-learn.
  • •Experience deploying and operating AI/ML solutions in production, including lifecycle support, and familiarity with big data/cloud platforms such as Databricks and AWS/Azure/GCP.
Experience:10+ yearsAIMachine learningSemantic data systemsKnowledge graphsEnterprise softwareCloud data platforms
Education:
Skills:CommunicationCollaborationCustomer-facing skillsAnalytical thinkingCross-functional collaboration
Tech Stack:PythonSQLPyTorchTensorFlowScikit-learnDatabricksSAP DatasphereSAP HANA CloudAWSAzureGoogle Cloud PlatformSAP HANA Cloud Knowledge Graph EngineSAP Business Data CloudSAP One Domain ModelSAP Graph APISAP Business Accelerator HubOWLRDFRDFSSKOS

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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