Principal Data and Applied Scientist (Montreal, Quebec, CA, H3B 0B3)

SAP
Montreal
Workplace: HybridFull timeCAD 144,600 - 322,500 annuallyFunction: Research & Scientific (R&D)Experience: 8+ yearsEducation: mastersSkills: ["Communication","Stakeholder management","Cross-functional collaboration"]

Build and scale SAP’s semantic, contextual foundation for accurate enterprise AI agents. You’ll design and maintain enterprise ontologies and semantic models, develop production RAG and knowledge-grounding pipelines, and create generative/LLM-based solutions using SAP and connected business data. Partner across product, engineering, and customer teams, and apply ML and statistical modeling to develop, evaluate, and continuously improve AI solutions in real enterprise environments.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
SAP
SAP
2 hours ago

Principal Data and Applied Scientist (Montreal, Quebec, CA, H3B 0B3)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Build and scale SAP’s semantic, contextual foundation for accurate enterprise AI agents. You’ll design and maintain enterprise ontologies and semantic models, develop production RAG and knowledge-grounding pipelines, and create generative/LLM-based solutions using SAP and connected business data. Partner across product, engineering, and customer teams, and apply ML and statistical modeling to develop, evaluate, and continuously improve AI solutions in real enterprise environments.
Location: Montreal
Workplace: Hybrid
Employment Type: Full time
Job Function: Research & Scientific (R&D)

Key Responsibilities

  • •Design and maintain enterprise ontologies and semantic models that enable accurate, grounded understanding of SAP and connected business landscapes.
  • •Build and scale production AI capabilities, including RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding.
  • •Develop generative AI/LLM-based solutions using enterprise business data, knowledge graphs, and business process intelligence.
  • •Apply ML, deep learning, and statistical modeling to develop, evaluate, and improve AI solutions using real-world enterprise datasets.
  • •Partner across product, engineering, business, and customer-facing teams to translate business challenges into AI solutions from concept through deployment and improvement.
Travel: Low travel

Pay and Benefits

Salary: CAD 144,600 - 322,500 annually

Key Requirements

  • •8+ years of experience in knowledge engineering, semantic data systems, applied AI, or data science.
  • •Master’s or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or a related quantitative field.
  • •Hands-on enterprise ontology/semantic model design, including proficiency in at least one graph query language (SPARQL, Cypher, or GQL) and understanding RDF vs property graph trade-offs.
  • •Hands-on GenAI systems experience with RAG, embeddings, vector databases, semantic retrieval, and enterprise knowledge grounding.
  • •Strong Python and SQL skills and experience deploying AI/ML solutions in production, including lifecycle support and continuous improvement.
Experience:8+ yearsAIMachine learningData scienceKnowledge graphsEnterprise software
Education:Master's in Computer Science, Applied Mathematics, Statistics, Engineering (or related quantitative field)
Skills:CommunicationStakeholder managementCross-functional collaboration
Languages:English
Tech Stack:PythonSQLPyTorchTensorFlowScikit-learnRAGEmbeddingsVector databasesSemantic retrievalLLMsLLM-based solutionsKnowledge graphsGraph query languageSPARQLCypherGQLRDFRDFSOWLSKOS

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
WebsiteLinkedInGlassdoor