Senior Manager, Data Analytics
New
J
JobgetherEcommerce, Retail
CanadaFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- 8+ years of professional experience; 5+ years of management experience
- Required Skills
- Data scienceData analytics
Requirements
- 8+ years of professional experience, ideally in data analytics within a high-growth consumer technology, ecommerce, or retail environment.
- 5+ years of management experience, including experience leading and developing experienced analysts or data scientists.
- Deep ecommerce, retail, or supply chain analytics expertise.
- Strong knowledge of KPIs covering inventory, order economics, pricing, unit economics, in-stock rates, and fulfillment efficiency.
- Demonstrated ability to balance people leadership with hands-on individual-contributor analytical work.
- Proven experience partnering with VP-level and executive stakeholders.
- Extensive experience with data analytics, big data technologies, and statistical modeling.
- Experience with data governance, data quality management, and data strategy.
- Genuine experience using AI to accelerate analytical and business outcomes.
- Strong strategic thinking, business judgment, and intellectual curiosity.
- Excellent communication skills.
- Strong ownership and organizational skills.
Responsibilities
- Lead, coach, and develop a team of five experienced analysts and data scientists.
- Own a meaningful portfolio of hands-on analytical work spanning ecommerce, supply chain, health, merchandising, inventory, and fulfillment.
- Partner directly with senior leaders and executives to identify opportunities and translate data into strategic recommendations.
- Define, maintain, and champion KPI frameworks and reporting standards across relevant business functions.
- Build and execute a prioritized analytics roadmap.
- Advance AI-native analytics capabilities, including self-service tools and AI-connected reporting.
- Establish high standards for modern, AI-forward analytics and encourage knowledge sharing.
- Solve complex business problems through statistical modeling and actionable insights.
- Strengthen data fluency across the organization.
- Maintain awareness of data governance, data quality, and data strategy principles.
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