Product Operations, AI & Insights ManagerDepartment: Product & Services
Employment Type: Full Time
Location: Toronto, ON
Compensation: CA$80,000 - CA$100,000 / year
DescriptionAs Product Operations, AI & Insights Manager at GS1 Canada, you are the operational backbone of the Product Management function. You enable a high-performing product organization by designing and maintaining the systems, processes, data infrastructure, and AI capabilities that allow product teams to operate at scale without sacrificing strategic focus or decision quality.
You own the end-to-end operational model-from intake and portfolio governance through analytics, measurement, and continuous improvement. You report to the VP of Product Management and work cross-functionally with Engineering, Design, Data, Finance, and Marketing to ensure product teams have what they need to deliver measurable outcomes.
GS1 Canada has defined a structured product operating model and is rolling it out across teams; this role owns the governance of it.
This is a hybrid role, requiring periodic in-person attendance.
Key ResponsibilitiesData Infrastructure, Measurement & Analytics- Define and maintain KPI frameworks and product success metrics across the product portfolio, distinguishing output measures (adoption, feature usage) from outcome measures (retention, subscriber satisfaction, business and financial impact).Establish and govern the analytics platform, ensuring data quality, accessibility, and accuracy so product managers can make evidence-based decisions with confidence.
- Implement and manage executive dashboards that translate product performance data into clear narratives for leadership, surfacing trends, risks, and opportunities requiring strategic attention.
- Own the NPS program: administer surveys, consolidate qualitative feedback, analyze sentiment and drivers, and present insights to Product Managers to inform their prioritization of product improvements.
Customer Intelligence Aggregation & Research Management- Establish a centralized research repository that consolidates customer insights from multiple sources: user interviews, market research, support tickets, usage patterns, competitive intelligence, and subscriber feedback.
- Synthesize fragmented feedback (from Teams threads, emails, support systems, and ad-hoc conversations) into structured, prioritized insights that inform product strategy.
- Partner with Subscriber Support and Account Management to surface field signals and operational friction that warrant product response.
Product Analytics & AI Workbench- Implement and optimize product analytics tooling (Pendo and related platforms), managing the technical stack to provide product teams with real-time usage visibility, behavioral analysis, and cohort performance tracking.
- Design and deliver ad-hoc analyses and insights that surface product opportunities, bottlenecks, and user behavior patterns; translate complex data narratives into clear, actionable recommendations.
- Evaluate, pilot, and scale AI and agentic system capabilities within the product organization-including generative AI for discovery acceleration, AI-assisted roadmapping, and agentic workflows for operational automation.
- Maintain the AI Workbench: curate AI skills and prompts, establish governance guidelines for responsible AI use, and build Product Management muscle around AI-assisted product development and decision-making.
Governance, Intake & Portfolio Management- Establish clear intake discipline: define what moves forward, what waits, and what gets declined; communicate decisions transparently; and track the evolution of ideas through the system.
- Establish portfolio management discipline: maintain visibility into active initiatives across all product teams, track dependencies, flag risks, and provide regular portfolio health reporting to executive leadership.
- Create and enforce product governance standards: documentation templates, decision-log practices, launch readiness checklists, and post-launch review processes that ensure consistent, high-quality execution across teams.
Tools, Process & Operational Excellence- Own the product management technology stack: evaluate tools, implement platforms, manage integrations (Pendo, road mapping, analytics, documentation systems), and ensure teams extract maximum value without tool sprawl or redundancy.
- Standardize processes across product teams: backlog management, sprint planning, customer discovery, stakeholder alignment ceremonies, and cross-functional collaboration. Reduce friction, eliminate rework, and maintain consistency as the team scales.
- Standardize communications and documentation: establish norms for how teams share decisions, maintain backlogs, record learnings, and communicate across functions. Ensure everyone knows where to find information and how to stay informed.
- Develop self-service capabilities for product insights: dashboards, templates, documentation, and training that allow product managers to access data and insights independently rather than waiting for ad-hoc analysis.
Product Manager Onboarding & Enablement- Support the onboarding and integration of new product managers into the organization: conduct orientation, share best practices, provide documentation of processes and expectations, and ensure new PMs feel confident in their first weeks
Skills, Knowledge & Expertise- 4+ years in product operations, product analytics, or related operational roles supporting product management teams or product-led organizations; or equivalent product management experience with deep analytics and operational discipline.
- Demonstrated expertise in designing and maintaining KPI frameworks, product analytics platforms, and measurement systems at scale; working knowledge of tools like Pendo, Amplitude, or similar analytics platforms. Experience leading intake, roadmap prioritization, and portfolio management processes in complex product organizations with multiple teams and competing priorities.
- Strong SQL and data analysis skills; ability to write queries, interpret results, and translate data into actionable product narratives.
- Proven ability to standardize and scale product processes, documentation, and governance without creating bureaucracy.
- Familiarity with AI/ML and emerging technologies, including hands-on experience with generative AI tools and agentic systems; pragmatic judgment about where AI adds value.
- Excellent written and verbal communication; ability to synthesize complex data into clear narratives for product managers, executives, and cross-functional partners.
- Knowledge of GS1 standards, data governance principles, or master data management is an asset but not required; willingness to build this depth quickly.
- Experience with product management tools (Jira, Confluence, or similar) and ability to evaluate and integrate new platforms into existing workflows.
