Data Scientist

This role leads the design and implementation of data architecture, capability development, and activation strategies at Canadian Tire. It involves overseeing data infrastructure, ensuring data governance, and enabling data-driven decision-making across the organization. The manager will collaborate with cross-functional teams to align data initiatives with business goals.

Als Expert Lead Data Strategy (Mensch) übernimmst du eine herausgehobene Expertenrolle und hilfst Kunden, komplexe Business-, Marketing- und Media-Herausforderungen in klare, umsetzbare Datenstrategien zu übersetzen – von der Fragestellung über Use Cases und Technologie-Roadmaps bis zur Anwendung. Du berätst Senior- und C-Level-Entscheider, konzipierst Audience-First-Strategien über First-, Second- und Third-Party-Daten und etablierst Data-Kollaborationen sowie Private Data Networks. Zudem bewertest und gestaltest du den Einsatz von Data Clean Rooms, CDPs und DSPs und verbindest Kunden-Roadmaps mit globalen Lösungen wie WPP Open, Open Intelligence und InfoSum.

This role involves conducting market research interviews and analyzing data in Angola. The analyst will collect primary data, manage survey logistics, and deliver insights to support client projects.

Develop and implement data governance frameworks and AI governance policies to ensure responsible and compliant use of data and AI across Xero. Collaborate with legal, data, and engineering teams to mitigate risks and uphold ethical standards.

This role takes ownership of a well-defined stream or mission, building and deploying AI agents and solutions while coaching junior consultants. The senior builder designs engaging learning experiences, prototypes functional AI solutions (no-code, low-code, vibe coding), and drives adoption through office hours and train-the-trainer programs. Success is measured by real adoption, team autonomy, and tangible changes in daily work.

This role leads AI adoption missions and programs, driving AI from experimentation to business transformation. The manager defines upskilling programs, builds agents and AI solutions (no-code, low-code, vibe coding), and manages teams, budgets, and client relationships. Responsibilities include scoping with L&D/HR, overseeing solution development, and structuring change management with KPIs and dashboards.

This role builds production-grade business applications and agents in partnership with an AI Product Manager. The engineer is responsible for frontend, backend, and APIs, integrating AI agents into business processes with human-in-the-loop controls, and ensuring monitoring and adoption post-production. The role requires tested code in Python or TypeScript and experience with coding agents.