Position: Data Science Co-op/Intern
Number of Position(s): 3
Duration: 4 Months
Date: January 4, 2027 - April 30, 2027
Location: Hybrid in Ottawa, CANADA
Education Requirements
Currently pursuing a Bachelor's or Master's degree, or a College diploma, at an accredited Canadian university or college in a relevant technical discipline. Preferred fields of study include Data Science, Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, Artificial Intelligence, Statistics, Mathematics, or other related programs.
You will:
- Design, develop, and evaluate AI-powered applications leveraging Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), and intelligent workflow automation technologies.
- Collaborate with engineering teams to analyze workflows, identify automation opportunities, and translate business requirements into practical AI-driven solutions.
- Develop software applications, APIs, and automation tools using Python and AI-assisted development platforms such as Cursor AI and GitHub Copilot.
- Analyze engineering and operational data to generate reports, dashboards, visualizations, and actionable insights that support data-driven decision making.
- Participate in Agile development activities, design reviews, AI adoption initiatives, workshops, and knowledge-sharing sessions across global engineering teams.
You must have:
- Strong programming experience in Python and familiarity with software development, automation frameworks, APIs, and application design principles.
- Knowledge of Generative AI concepts, including Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and agentic workflows.
- Experience using modern AI-assisted development tools such as Cursor AI, GitHub Copilot, or similar platforms to improve software development productivity.
- Understanding of data analytics, statistics, data modeling, and visualization techniques obtained through academic coursework, projects, or practical experience.
Strong analytical, problem-solving, communication, collaboration, and continuous learning skills with a demonstrated interest in AI and automation technologies.
Nice-to-Have Qualifications:
- Experience building AI-powered applications using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar technologies.
- Exposure to AI guardrails, LLM evaluation, observability, tracing, monitoring solutions, and AI application lifecycle management practices.
- Experience with enterprise application development, dashboards and visualization platforms (Grafana, Splunk, Power BI), Git-based development workflows, CI/CD pipelines, or participation in hackathons, research projects, or AI-related extracurricular activities.