About the role#
As a Data Services AI Co-op Student, you will work directly with operational workflows including facility data aggregation, production system integration, and client onboarding. You will be responsible for identifying opportunities to streamline processes and building tools that improve efficiency, data quality, and team productivity. You will translate operational challenges into structured solutions, build prototypes, and document your work for long-term team use.
What you'll do#
- Analyze and map existing workflows, such as production triage, client onboarding, and facility data issue resolution.
- Identify manual, repetitive, or rules-driven tasks suitable for automation or AI-assisted routing.
- Build automation workflows using Azure native tools, scripting, and approved AI tools.
- Develop solutions to extract information from structured and unstructured sources, automate ticket creation, and implement agentic workflow patterns.
- Create tools to monitor interval data for missing information, communication issues, and recurring data-quality exceptions.
- Work from a prioritized backlog of AI, automation, and Data Services improvement projects.
- Collaborate across Data Services, Business Development, Software, and IT teams to deliver and demo improvements.
What you'll need#
- Currently enrolled in a recognized co-op program in Computer Science, Engineering, Data Analytics, Information Systems, AI, or a related field.
- Strong analytical and problem-solving skills with the ability to break down ambiguous operational problems.
- Basic scripting or programming experience (e.g., Python, SQL, JavaScript, or equivalent).
- Comfort working with data in Excel, databases, APIs, reports, or operational systems.
- Strong communication and documentation skills.
- Demonstrated ownership mindset and ability to learn new technologies quickly.
- Preferred: Exposure to Power Automate, Power BI, AI/ML concepts, or workflow mapping experience.
Location & details#
- Location: Mississauga, ON, Canada.
- Term: Fall 2026 (September – December).
- Work Modality: On-site (5 days per week).
- Employment: Full-time, paid position.
