About
AI, data and analytics—with operational accountability.
A senior-specialist approach that keeps technical implementation close to delivery decisions, evidence and review.
Working philosophy
Good systems expose their boundaries.
The work centres on the decisions that make AI useful: what evidence it can see, where model judgment is appropriate, what remains deterministic, how ambiguity is handled and who approves the result.
The result is a deliberate blend of hands-on technical depth and delivery leadership, with consequential acceptance kept human-accountable.
Education & certifications
The formal foundation.
- Master of Data Science & Analytics — University of Calgary, Financial & Energy Markets (2024–2025)
- Bachelor of Commerce — McGill University, Information Systems (graduated with distinction)
- Certifications — Claude Certified Architect (CCA) Foundations, in progress (2026) · Anthropic Academy, in progress · Power BI · Syniti (SynitiONE, SKP, Migrate, MDM)