About The Position

As a member of the senior leadership team, the Sr. Director, Analytics & Insights is accountable for building and leading a best-in-class analytics function that drives commercial strategy, unlocks growth, and enables data-driven decision-making across all areas of the Roots business. Reporting to the Chief Commercial Officer, this leader plays a pivotal role in shaping how Roots identifies and pursues its biggest opportunities — across channels, categories, customers, and markets. This role is responsible for establishing the organization's analytics operating model — including a centralized data and engineering capability and embedded analyst partnerships within Ecommerce, Retail, and Merchandising — and for ensuring that the right insights reach the right people at the right time. As a trusted strategic partner to the CCO and the broader commercial leadership team, the Sr. Director translates data into a competitive advantage: surfacing growth opportunities, informing investment decisions, and bringing an evidence-based perspective to every major commercial initiative. This leader brings both technical credibility and deep commercial acumen, and is as comfortable shaping channel strategy as they are working through a data model with their team.

Requirements

  • 15+ years of progressive analytics or data leadership experience, with a minimum of 5 years leading analytics teams in a retail, ecommerce, or consumer brand environment.
  • Demonstrated track record of building and scaling analytics functions that have driven measurable commercial outcomes — revenue growth, margin improvement, customer retention, or channel expansion.
  • Deep expertise across the retail commercial analytics landscape — including ecommerce performance, customer and loyalty analytics, merchandising and inventory analytics, marketing effectiveness, and competitive intelligence.
  • Proven ability to act as a strategic growth partner to commercial leaders — not just reporting performance, but proactively identifying opportunities, shaping strategy, and influencing investment decisions through data.
  • Strong technical foundation with hands-on experience in SQL, data modelling, and BI platforms (experience with Snowflake is a strong asset); able to engage credibly with data engineers and evaluate technical approaches.
  • Exceptional executive communication and storytelling skills — able to distill complex analytical findings into compelling commercial narratives, present with confidence to the C-suite and Board, and drive alignment through insights.
  • Proven ability to operate in an embedded analytics model, building trusted relationships with functional leaders while maintaining centralized standards and a cohesive team culture.
  • Experience building and managing structured analytics operating rhythms, including regular reporting cadences, ad-hoc request processes, and roadmap planning.
  • Bachelor's degree in a quantitative field (Mathematics, Statistics, Computer Science, Economics, or related); Master's degree or MBA is an asset.
  • Demonstrated curiosity and working knowledge of AI and machine learning applications in a retail or commercial context — including experience evaluating or deploying predictive models, generative AI tools, or automation capabilities that have driven measurable business outcomes.

Nice To Haves

  • Master's degree or MBA is an asset.

Responsibilities

  • Act as a strategic growth partner to the CCO and commercial leadership team — proactively identifying opportunities to accelerate revenue, expand market share, improve margin, and deepen customer relationships across all channels.
  • Lead the development of commercially-driven analytics that go beyond performance reporting — surfacing white space, sizing opportunities, and informing investment decisions across Ecommerce, Retail, Merchandising, and Marketing.
  • Bring a forward-looking perspective to the business: translate trends in customer behaviour, channel performance, and competitive positioning into clear strategic recommendations for the senior leadership team.
  • Influence the annual planning process and long-range strategic plan with a data-driven point of view on where Roots should grow, invest, and optimize.
  • Champion a test-and-learn culture across commercial functions — developing experimentation frameworks, supporting A/B testing, and building the organization's ability to make faster, evidence-based decisions.
  • Stay at the forefront of emerging analytics technologies and AI capabilities — evaluating where tools such as generative AI, predictive modelling, and machine learning can be applied to accelerate insight generation, improve forecasting accuracy, and create competitive advantage for Roots.
  • Serve as the primary analytics partner to Ecommerce, Retail, Merchandising, and Marketing — embedding analytical thinking into their strategies, roadmaps, and operating rhythms.
  • Partner with Marketing and CRM to unlock customer analytics capabilities that drive loyalty, retention, and lifetime value growth — including segmentation, win-back, personalization, and loyalty program optimization.
  • Collaborate with Merchandising and Planning on assortment strategy, pricing architecture, and inventory investment decisions; bring an analytical lens to buying and open-to-buy processes.
  • Support Ecommerce in building a performance marketing and digital analytics capability that connects media spend to revenue outcomes, and identifies the highest-ROI levers for growth.
  • Partner with Retail to identify operational and commercial opportunities at the store level, including conversion improvement, traffic optimization, and comp store growth strategies.
  • Lead, coach, and develop a team of analytics professionals across central and embedded functions, fostering a culture of intellectual curiosity, commercial thinking, accountability, and continuous improvement.
  • Establish clear roles, responsibilities, and performance expectations for both central team members and business-embedded analysts; ensure alignment and collaboration across the full team.
  • Champion the professional growth of each team member through regular feedback, development planning, and exposure to enterprise-wide commercial priorities.
  • Build for the future — identify capability gaps, develop succession plans, and invest in the skills needed to grow the analytics function as the business scales.
  • Define and execute the analytics strategy for Roots, including the team's operating model, prioritization framework, and approach to self-serve analytics across the business.
  • Own the organization's reporting cadence — from daily revenue pulses to quarterly business reviews — ensuring that the business operates from a single, trusted source of truth.
  • Establish and govern standards for data definitions, metric frameworks, and analytical methodology across all functions to drive consistency and confidence in reported numbers.
  • Build and maintain the analytics roadmap, balancing short-term commercial priorities with longer-term infrastructure investments and capability development.
  • Champion a structured approach to ad-hoc analytics requests — including intake, prioritization, SLA management, and the identification of recurring questions that should become standing reports or dashboards.
  • Oversee the data engineering and BI function, ensuring that data pipelines, Snowflake data models, and dashboard infrastructure are reliable, scalable, and accessible to business users.
  • Partner with Technology and Finance to evaluate and evolve the analytics tech stack, including BI tooling, data pipeline infrastructure, and data governance platforms.
  • Champion data quality and integrity across all reporting; ensure issues are identified proactively and resolved with urgency.
  • Drive the adoption of self-serve analytics tools and capabilities that reduce dependency on the central analytics team for routine reporting needs.
  • Identify and evaluate opportunities to integrate AI and machine learning into the analytics stack — including demand forecasting, customer propensity modelling, personalization, and automated anomaly detection — and build a roadmap for adoption that is practical, scalable, and aligned to business priorities.

Benefits

  • Accommodations are available for applicants throughout the recruitment process.
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