Sr. Director, Business Intelligence and Analytics

Responsibilities

• Build and Lead the Business Intelligence and Analytics Function
• Build, lead, and mature GS1 Canada’s business intelligence and analytics capability, including enterprise reporting, subscriber and sector analytics, product and service usage analytics, market intelligence, and growth insights.
• Establish a trusted and consistent single version of the truth by aligning data definitions, metrics, dashboards, and reports across business units
• Lead enterprise dashboards, executive scorecards, and recurring insight products covering subscriber growth, retention, churn, adoption, engagement, service usage, sector penetration, revenue performance, and strategic execution.
• Advance the function from descriptive reporting to diagnostic, predictive, and prescriptive insight that identifies drivers, anticipates risks and opportunities, and recommends action.
• Establish standards for analytical quality, metric definitions, dashboard governance, documentation, reproducibility, and executive communication.
• Partner with Technology, Data Governance, and business teams to improve data accessibility, quality, reliability, and fitness for analytical and AI use.

Lead Subscriber, Sector and Market Intelligence

• Build an integrated intelligence capability that combines subscriber and operational data, sector insight, competitive intelligence, and external market trends.
• Monitor changes in subscriber expectations, digital and agentic commerce, product data management, regulation, sustainability, 2D barcode adoption, AI-enabled data management, and other developments affecting GS1 Canada’s relevance and growth.
• Synthesize quantitative and qualitative signals from sector boards, working groups, subscriber interactions, support channels, research, and industry forums in partnership with relevant business teams.
• Identify enterprise-wide patterns and sector-specific needs, and provide regular executive briefings on market shifts, subscriber expectations, competitors, opportunities, and strategic risks.
• Recommend where insights indicate a need to adjust strategic focus, product priorities, positioning, education, or market engagement.

Own the Enterprise KPI and Measurement Framework

• Define and maintain the enterprise KPI framework, aligned to strategy, subscriber value, growth, adoption, financial performance, and operational outcomes.
• Set consistent definitions and ownership for core measures, including subscriber growth, retention, churn, engagement, adoption, product and service usage, sector penetration, revenue trends, and strategic progress
• Partner with Finance and functional leaders to ensure measures are reliable, decision-useful, and consistently applied across executive, functional, and sector reporting.
• Identify gaps or inconsistencies in measurement and recommend improvements to data, instrumentation, reporting, and accountability.
• Focus leadership attention on the few measures that matter most, connecting activity to subscriber outcomes, growth impact, and strategic value.

Lead the AI-Enabled Transformation of Analytics

• Develop and execute a multi-year roadmap to transform the analytics function through AI, aligned with enterprise strategy, the AI Council, and GS1 Canada’s technology and data priorities.
• Prioritize high-value use cases such as automated data preparation and reporting, insight synthesis, anomaly detection, forecasting, segmentation, churn and propensity analysis, and conversational or self-service analytics.
• Redesign analyst workflows and roles to combine automation with human judgment, enabling the team to spend less time producing reports and more time interpreting results, advising leaders, and driving action.
• Establish a disciplined path from experimentation to production, including use-case intake, value assessment, pilots, validation, adoption planning, controls, and scaling.
• Partner with Technology and Data Governance on approved tools, architecture, secure data access, semantic models, data quality, integration, and production support; retain business ownership of analytical use cases, adoption, and outcomes.
• Partner with the AI Council, Privacy, Legal, Cybersecurity, and Data Governance to ensure appropriate human oversight, transparency, confidentiality, intellectual property protection, bias testing, accuracy, and responsible use
• Build team capability in AI-assisted analysis, prompt and context design, model limitations, validation, documentation, and effective human review.
• Measure transformation value through adoption, time-to-insight, productivity, analytical quality, decision impact, and measurable business outcomes.
• Prepare executive and Board materials that clearly communicate strategic progress, performance trends, subscriber outcomes, growth opportunities, and emerging risks.
• Translate complex analysis into concise narratives that connect metrics to strategy, market conditions, implications, and decisions required.
• Support executive decision-making by identifying the most important insights, dependencies, risks, options, and recommended actions.
• Provide Product and Subscriber Management with insight on adoption, usage, lifecycle performance, acquisition, retention, churn, account health, sector performance, and growth potential.
• Support Marketing, Product Marketing, Industry Relations, and Community Engagement with analysis of awareness, engagement, campaign effectiveness, market positioning, sector signals, and subscriber sentiment.
• Align revenue and performance analytics with Finance while preserving Finance’s accountability for budgeting, forecasting, accounting, and financial controls.
• ·Promote a culture in which data, evidence, and insight consistently shape leadership discussions, priorities, and resource decisions.

Build and Lead a High-Performing Analytics Team

• Coach analysts to progress from report production to insight generation, storytelling, analytical judgment, business partnership, and strategic advisory work.
• Set clear objectives and quality standards, manage performance, allocate capacity to the highest-value work, and establish transparent intake and prioritization practices.

Requirements

• Strong enterprise strategy, business intelligence, analytics, and performance management capability.
• Strong understanding of practical AI applications in analytics, including generative AI, predictive methods, automation, conversational analytics, and human-in-the-loop control
• Strong understanding of subscriber or customer analytics, including segmentation, adoption, engagement, retention, churn, lifetime value, and market opportunity.
• Strong people leadership with the ability to elevate the quality, relevance, efficiency, and strategic impact of team outputs.
• Strong executive communication skills, including Board-level writing, presentation, data storytelling, and facilitation

Key Responsibilities

Provide Executive and Board-Level Insight

Serve as a trusted enterprise advisor by providing balanced, objective, transparent, and analytically rigorous insight.

Partner Across the Organization to Enable Insight-Driven Decisions

• Act as a strategic partner to Product, Subscriber Management, Finance, Marketing, Industry Relations, Community Engagement, Technology, Operations, and Data Governance
• Define the team structure, roles, capabilities, workflows, service model, and operating rhythms required for a modern enterprise analytics function.
• Create a high-performance culture grounded in curiosity, objectivity, experimentation, collaboration, accountability, and subscriber value.
• Develop talent, succession plans, and future-ready skills across business intelligence, analytics, market intelligence, and AI.

Skills, Knowledge & Expertise

• 10+ years of progressive experience in business intelligence, analytics, market intelligence, enterprise performance, strategy, or related business leadership roles.
• Demonstrated experience building or transforming a business intelligence or analytics function, including changes to operating models, processes, tools, and team capabilities.
• Demonstrated experience leading the adoption of AI, machine learning, automation, or advanced analytics in business workflows and taking use cases from pilot to sustained use.
• Experience leading and developing analysts and influencing cross-functional teams in a complex organization.
• Proven ability to translate data and market signals into executive-level insight, decisions, and strategic recommendations.
• Experience developing enterprise KPIs, dashboards, scorecards, performance frameworks, and self-service analytics
• Experience analyzing customer or subscriber behaviour, retention, churn, adoption, engagement, revenue trends, market opportunity, or product and service performance.
• Experience supporting executive leadership and Board-level reporting.
• Experience in B2B, data services, SaaS, digital commerce, retail, healthcare, supply chain, standards, or member- or subscriber-based organizations is an asset.

Skills & Capabilities

• Demonstrated change leadership and the ability to redesign work, build adoption, develop new capabilities, and realize measurable value from new technology.
• Strong analytical judgment, including the ability to distinguish signal from noise, challenge assumptions, validate outputs, and communicate uncertainty.
• Ability to translate complex data into clear business narratives, executive-ready insights, and actionable recommendations.
• Strong cross-functional collaboration and influence without direct authority.
• Sound understanding of data governance, privacy, security, responsible AI, metric consistency, reporting standards, and analytical quality control.
• Ability to build structure

Compensation

CA$145,000 - CA$165,000 / year