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Manager, Finance Data and AI

Remote / Online - Candidates ideally in
North Vancouver, BC, Canada
Listing for: Arc'teryx Equipment
Remote/Work from Home position
Listed on 2026-06-17
Job specializations:
  • IT/Tech
  • Finance & Banking
Salary/Wage Range or Industry Benchmark: 100000 - 125000 CAD Yearly CAD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Arc’teryx is seeking a Manager, Finance Data and AI to join the Finance Transformation, Risk & Controls team. This role is responsible for advancing the use of artificial intelligence and modern data capabilities across the Finance organization.

The successful candidate will be involved in designing, building, and deploying AI-enabled workflows that improve efficiency and decision‑making within Finance, while also serving as the primary intake point for data and reporting requests originating from Finance teams. The role partners closely with the Data and Analytics (IT) team to scope, prioritize, and deliver data solutions.

This is a high‑autonomy role suited to a self‑directed professional who combines technical proficiency with strong program execution and stakeholder management. The successful candidate will lead through technical credibility, sound judgment, and the ability to influence cross‑functional partners.

This role is based out of our North Vancouver office and is open to hybrid remote work. Candidates must be eligible to work in Canada.

Meet Your Future Team

The Finance Transformation, Risk & Controls team leads the modernization of Finance at Arc’teryx – driving improvements across Finance business processes, systems, AI, governance, and risk management. The team partners across Finance and the broader business to ensure that how we operate, what we deliver, and how we manage risk continues to evolve as the company grows.

Designing and Delivering Self‑Serve AI Workflows
  • Identifying, scoping, and prioritizing opportunities to apply artificial intelligence and automation across Finance processes and workflows.
  • Designing and building self‑serve AI‑enabled workflows using tools such as Microsoft Copilot Studio, Microsoft 365 Copilot, Power Automate, Claude, and related technologies.
  • Leading end‑to‑end delivery of AI workflows, including requirements gathering, prototyping, user acceptance testing, deployment, and transition to business owners.
  • Developing and maintaining reusable assets, including a finance‑specific prompt library and pattern library, to accelerate future delivery.
  • Establishing and upholding appropriate governance, risk assessment, and compliance practices for all AI solutions.
Building and Leading the AI Community Within Finance
  • Standing up and leading a small, cross‑functional core delivery team that designs, builds, and ships AI solutions in close partnership with the business.
  • Establishing and curating a peer network of AI advocates embedded across Finance teams – individuals who pilot new solutions, share what they learn, and bring forward ideas from their teams.
  • Launching and sustaining a broader community of practice across the Finance organization that supports shared learning, knowledge exchange, prompt sharing, and ongoing engagement with the program.
  • Defining the purpose, cadence, and operating rhythm of each group, recruiting and onboarding members, and keeping participation engaged and productive over time.
  • Acting as the principal leader and driver of these groups, ensuring they continue to deliver value and adapt as the program matures.
Coordinating Data and Reporting Demand
  • Serving as the front door for data and reporting requests originating from Finance.
  • Triaging, scoping, and prioritizing incoming requests in collaboration with the Information Technology Data and Analytics team, and maintaining a transparent backlog so requesters have clear visibility into status and timelines.
  • Translating business problems into clear, well‑structured requirements that the Information Technology Data and Analytics team can act upon, and managing stakeholder communication through delivery to ensure successful adoption.
  • Establishing and publishing a clear scope rubric – what is in scope for self‑serve AI workflows, what is in scope for IT Data and Analytics build, and what is out of scope – to help requesters and stakeholders engage the process effectively.
  • Promoting a self‑serve culture by enabling business users to confidently use approved tools, reducing reliance on one‑off requests over time.
Driving Adoption, Enablement, and Change
  • Applying data classification and sensitivity…
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