Definition: A Data Scientist role in Canada pays a median salary of C$130k per year (juniors C$90k, seniors C$200k) with an AI replacement risk of 7/10. The role requires Python, Machine Learning, Statistics, plus emerging AI-collaboration skills.
Canada's data science sector is projected to grow 22% through 2026, outpacing most other tech roles, and demand remains concentrated in Toronto, Vancouver, and Montreal where major tech hubs and financial institutions compete aggressively for talent. If you're pursuing this path, understand that employers here increasingly expect both statistical rigor and business acumen—they want scientists who can translate findings into revenue or cost savings, not just build models. The salary range typically spans $85K–$140K depending on experience and location, though senior roles at major banks or tech firms push higher. Entry barriers are real: most positions require a relevant degree (statistics, computer science, mathematics) plus demonstrated portfolio work, though bootcamp graduates do break in with exceptional projects. Your competition includes both domestic talent and international candidates on work permits, so differentiation through specialized skills (NLP, computer vision, MLOps) matters significantly. Below, you'll find current openings matching your profile, interview questions from actual hiring managers, and skill gaps to address before applying.
| Level | Salary | Years' Experience |
|---|---|---|
| Junior | C$90k | 0–2 |
| Median | C$130k | 3–6 |
| Senior | C$200k | 7+ |
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AI Threat Score: 7/10. AutoML and Code Interpreter automate notebook work; problem framing and ML productionisation remain.
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