Build, validate, and deliver analytics and machine learning solutions that translate complex data into clear insights and recommendations.
Write production-quality code that is stable, testable, and maintainable; contribute to shared standards through code reviews and documentation.
Apply sound statistical and machine learning methodology (e.g., experiment design, appropriate validation, model evaluation, monitoring) and continuously improve how we measure quality and impact.
Work independently on scoped problems—from ambiguity to implementation—taking ownership of technical tasks and driving them to completion.
Recommend and use appropriate tools, packages, and libraries to solve problems efficiently and reliably.
Partner closely with stakeholders across the organization to define success metrics, communicate trade-offs, and enable data-driven decisions.
Support and elevate teammates by collaborating on technical challenges, sharing best practices, and contributing to a learning culture.
Help the team stay focused on priorities by raising risks early, aligning on scope, and contributing to the technical direction and evolution of our approaches and platforms.
Maintain and improve data science tools and platforms, helping ensure efficiency, reliability, and repeatability of our work.

Degree in a relevant discipline (e.g., mathematics, engineering, operations research, statistics, geomatics, AI) or an equivalent combination of education and experience.
2+ years of experience in advanced statistics, data mining, and/or text mining, with evidence of delivering real-world outcomes.
Strong Python skills and Git-based development practices (e.g., version control, peer review); experience writing tests and producing clear technical documentation.
Solid understanding of machine learning methods and when to use them; comfortable explaining results and limitations to both technical and non-technical audiences.
Strong problem-solving skills and comfort operating in partially defined problem spaces.
Strong communication, organizational, and time management skills in a multi-project environment.
No Canadian work experience required however must be eligible to work in Canada.

Flexible work arrangements and a hybrid work model
Possibility to purchase up to 5 extra days off per year
Multiple benefits offered to support physical and mental wellbeing, including telemedicine, Wellness account and much more
Share plan & other savings: up to 12% of salary or even more (ask how you could earn guaranteed income for life)

Data Scientist II

Key skills