Data Scientist

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. ResponsibilitiesDesign 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 SkillsMaster’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 SkillsFamiliarity with LLMs (., 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 RequirementsMust 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.