Fujitsu Canada is seeking a full-time, permanent Data Scientist to support enterprise-scale Knowledge Management (KM) modernization projects. This role focuses on AI/ML/NLP development, semantic enrichment, and data transformation in hybrid environments, contributing to the delivery of intelligent, scalable KM solutions.
Top Skills:
• Master's degree in data science, Artificial Intelligence, Machine Learning, or Computational Linguistics.
• Proficiency in Python and libraries such as TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers, Pandas, and lxml.
• Experience with supervised, unsupervised, and reinforcement learning models.
• Expertise in NLP techniques including tokenization, entity recognition, topic modeling, and semantic search.
• Experience with knowledge graphs and semantic enrichment.
• Strong understanding of XML structure, namespaces, and DOM manipulation.
• Experience with relational databases (PostgreSQL, Oracle, SQL Server) and normalized schema design.
• Familiarity with Git for version control and collaboration.
• Experience with Azure Cognitive Services and DevOps pipelines.
• Experience in regulated or public sector environments.
Responsibilities
• Design and implement AI/ML models for semantic search, contradiction detection, and content rewriting.
• Build and query knowledge graphs using RDF, SPARQL, and ontology design.
• Develop and optimize XSLT stylesheets and XPath expressions for XML transformation.
• Author and manage structured content using DITA XML and document-as-code principles.
• Design and execute Extract, Transform, Load (ETL) workflows using Python and tools like Talend or Apache NiFi.
• Conduct data lineage and metadata management to ensure traceability and integrity.
• Collaborate with cross-functional teams including architects, linguists, and content authors.
• Support iterative development cycles, rapid prototyping, and continuous integration.
• Integrate AI frameworks with SharePoint Online, Microsoft 365, and workflow automation tools.
Mandatory Skills
• Master's degree in Data Science, Artificial Intelligence, Machine Learning, or Computational Linguistics.
• Proficiency in Python and libraries such as TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers, Pandas, and lxml.
• Experience with supervised, unsupervised, and reinforcement learning models.
• Expertise in NLP techniques including tokenization, entity recognition, topic modeling, and semantic search.
• Experience with knowledge graphs and semantic enrichment.
• Strong understanding of XML structure, namespaces, and DOM manipulation.
• Experience with relational databases (PostgreSQL, Oracle, SQL Server) and normalized schema design.
• Familiarity with Git for version control and collaboration.
• Experience with Azure Cognitive Services and DevOps pipelines.
• Experience in regulated or public sector environments.
Nice to Have Skills
• Familiarity with LLMs (e.g., GPT-4, Claude) for content generation and summarization.
• Experience with FAISS or Pinecone for semantic clustering.
• Exposure to FrameNet and other linguistic resources for semantic understanding.
• Experience with shell scripting, Typescript, Scala, or R.
• Use of Power BI, Tableau, or Quicksight for post-migration analytics.
• Understanding of bias mitigation, explainability, and responsible AI practices.
• Experience with contradiction detection and semantic validation.
• Familiarity with document chunking for retrieval-augmented generation (RAG).
General Requirements
• Must reside in the Gatineau area in Quebec.
• Hybrid work arrangement - onsite at least three days per week, with additional days as needed.
• Strong organizational and time management skills.
• Commitment to quality and attention to detail.
• Ability to work independently and collaboratively.
• Willingness to learn new tools and technologies.
• Eligibility for Reliability Security status; minimum five years' residency in Canada.
• Experience working in a multicultural or multilingual environment.
• Familiarity with agile or other modern project management methodologies.
• Previous experience in a remote or hybrid work setting.
