Responsibilities

• Own performance tracking, reporting, and analysis for marketing channels or programs, building reliable, well-structured work that stakeholders can act on with confidence
• Design and analyze experiments to evaluate channel effectiveness, including A/B tests and incrementality frameworks
• Build and maintain dashboards and reporting in Looker or similar tools that make it easy for growth teams to self-serve on key metrics
• Contribute to LTV and forecasting models, supporting the team's ability to connect paid marketing spend and lifecycle activity to downstream revenue impact
• Proactively flag measurement gaps, data anomalies, and analytical risks and bring proposed solutions
• Translate complex analysis into clear, well-scoped narratives for stakeholders across Growth and Finance, adjusting depth and framing to your audience

Requirements

• 3–5 years of experience in a marketing analytics, growth analytics, or closely related data role, ideally at a consumer-focused or high-growth technology company
• Strong, independent SQL skills - you can dive into an unfamiliar data domain, write accurate and efficient queries, and know when something looks off
• Solid grounding in marketing measurement concepts: channel performance metrics, attribution approaches, and advanced measurement approaches (incrementality, media mix)
• Experience building reporting and dashboards in a BI tool (Looker, Tableau, or similar)
• Comfortable working with experimentation concepts; you understand what makes a test valid and what can make results misleading
• Strong analytical communication skills: you can identify the right level of detail for your audience and write up findings that earn buy-in, not just acknowledgment
• Fluency with AI tools to accelerate analysis and reporting - for example, using LLMs to speed up SQL drafting, QA logic, or summarize findings, while still knowing when to verify outputs against your own judgment

Preferred

• Experience across both paid and email/lifecycle marketing programs
• Experience in mobile analytics
• Experience with Python or R for statistical analysis or modeling
• Experience with GA4 or similar web analytics platforms
• Experience using AI tools to automate parts of the analytics workflow - for example building agents or scripts that pull data, run recurring QA checks, or auto-generate reporting summaries