Data Science Co-op/Intern

Nokia
Ottawa, Ontario, CanadaPosted Sep 11, 2026
Data Science / ML

About the role

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.

RESPONSIBILITIES

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.

QUALIFICATIONS

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 da

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