Responsibilities

• Strategic Leadership: Define and lead the marketing analytics vision, roadmap, and long-term strategy for the Product, Hardware, Store and Services lines of business.
• Establish measurement frameworks to evaluate owned and earned channel performance and customer acquisition effectiveness.
• Partner with Marketing, Product, Finance, and Data teams to align analytics initiatives with business goals.
• Analytics & Insights: Translate complex data into clear, actionable insights for senior stakeholders across a broad range of analytic modalities.
• Oversee the implementation of analytics models, including attribution, incrementality testing, and forecasting in partnership with engineering.
• Identify growth opportunities and performance optimization strategies across owned and earned media channels.
• Data Infrastructure & Tools: Own the strategy for the evolution of marketing data infrastructure that ensures scalability, accuracy, and accessibility.
• Define requirements and prioritization for Data Engineering teams to build and maintain pipelines, dashboards, and reporting systems.
• Evaluate and implement analytics tools and platforms to enhance measurement capabilities.
• Performance Optimization: Lead ongoing performance analysis across channels such as SEO, organic social media engagement, CRM, and on-console messaging.

Requirements

• 10+ years of experience in marketing analytics or related fields.
• Proven leadership experience managing high-performing analytics teams.
• Deep expertise in digital marketing channels and measurement methodologies, especially earned and owned media measurement.
• Strong analytical and problem-solving skills.
• Experience with attribution models, experimentation design, and statistical analysis.

Preferred

• Proficiency in SQL, Python, or similar tools.
• Experience in a high-growth or technology-driven environment.
• Familiarity with marketing platforms and analytics tools (e.g., GA4, Adobe Analytics, Looker).
• Advanced degree in a quantitative field (e.g., Statistics, Economics, Computer Science).