Data Scientist Intern - Water (Fall 2026)

Learning begins in the classroom but there’s no better place to gain real-world experience than with Stantec. Interns are an integral part of our teams, working to solve some of the world's most complex challenges.

As an intern, you’ll work alongside our experienced practitioners and with our clients and communities. This hands-on experience will equip you with practical skills, build your network, and provide opportunities that set you up for success.

This Data Science Intern will work on a range of projects focused on the implementation and advancement of research and digital tools and technologies focused on the water, wastewater, biosolids and energy sectors.  The intern will work closely with Water BOU’s data strategy manager, machine learning leader, director of innovation and technology and other team members.  Collaborate with the Water OI&T research and engineering team to design and develop methodologies and systems employing data exploration (EDA), hypothesis testing and data modeling (e.g. advanced statistics, machine learning, data analytics) in digital solutions.  The intern will contribute to the initiatives such as Water BOU’s Digital Transformation and development of digital solutions to support project delivery.  The intern will report to an Innovation Portfolio Manager in OI&T. This position can be remote,

Knowledge, Skills, and Abilities:

• Strong analytical skills.
• Programming knowledge and willingness to further expand knowledge capital and skill sets (e.g., python, MATLAB, etc.)
• Excellent oral and written communication skills.
• Excellent problem-solving skills.
• Ability to independently manage multiple priorities.
• Strong interpersonal skills and ability to work within all levels of an organization.
• Expert level Microsoft product user; Office365 Suite
• Willingness to develop and enhance low-code/no-code skill sets
• Highly curious and willingness to take intellectual risks
• Team oriented with earnest willingness to share ideas with OI&T team and explore through quick test-and-learn approaches