Scientifique des données - Données et Intelligence artificielle (IA appliquée) / Data Scientist[...]

Qualifications

Being part of Air Canada is to become part of an iconic Canadian symbol, recently ranked the best Airline in North America. Let your career take flight by joining our diverse and vibrant team at the leading edge of passenger aviation.

As a Data Scientist Data & AI (Applied AI) at Air Canada, you will be embedded in cross-functional team and will contribute to the MLOps pipeline and processes to scale and deploy ML, Optimization and Agentic solution. We are looking for a Data Scientist to help us build and operate our ML, Optimization and agentic platform to increase reliability and governance. You will primary be working with data scientist, research scientist, solution architect and system integrator to contribute to the architecture and the products powered by advanced analytics and AI.

The ideal candidate will possess a strong foundation in software design principles, with a proven track record of designing, developing, and deploying robust y systems. The candidate will also be well-versed in model version control, deployment pipelines, and monitoring standards. The candidate is expected to have some level on knowledge into the inner working of the models instead of treating them as black boxes.

You will join the Data Science & AI Team, a central group within Air Canada’s IT organization, building machine learning and optimization solutions for internal business units such as Revenue Management, Network Planning, Operations, Maintenance, and Cargo but also customer facing solution. Collaboration with both technical and non-technical stakeholders is essential as you deliver production-grade applications.

All initiatives follow an agile methodology, with 2-to-3-week sprints and incremental releases leading to the final production deployment. This approach fosters continuous improvement, adaptability, and close alignment with business needs.

Qualifications

• Master’s or PhD in Data Science, Computer Science, or a closely related field, or equivalent and 5+ relevant working experience.
• Proven experience managing the full MLOps lifecycle, including automated training pipelines, feature store integration, batch and real-time inference, model monitoring, and data / code versioning best practices.
• Strong proficiency in Python and its ML / data ecosystem, including libraries such as Pandas, scikit-learn, MLflow, PySpark, TensorFlow, and others.
• Hands-on experience with Azure’s ML and AI services, including Azure Machine Learning, Azure Databricks, Azure Data Factory, Azure Functions, Azure OpenAI, and Azure AI Search, along with their SDKs.
• Experience building CI / CD pipelines for ML workflows using Git-based platforms such as Azure DevOps and GitHub Actions.
• Working knowledge of large language models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG) architectures, and open-source frameworks for generative AI.
• Strong problem-solving skills with the ability to work independently and collaboratively in cross-functional teams.
• Demonstrated ability to standardize and productize ML solutions into reusable components and scalable infrastructure.
• Excellent communication skills, both written and verbal, with the ability to convey complex technical concepts to diverse audiences.

Asset Qualifications

Please refer to the Air Canada Careers page for full job details.

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