Growth Data Analytics Lead

About the role

This role exists to turn data into decisions that change the trajectory of the business and take charge of moving key growth metrics like conversion, retention and monetization. You sit at the intersection of marketing, product, tech, and leadership - owning analytical truth across the funnel and transforming data into clear, opinionated recommendations.

What you'll do

• Proactively point the business toward where data indicates opportunity, risk, or misallocation of effort and turn data into clear, opinionated recommendations that influence commercial decisions.
• Go beyond what happened to explain why, what to do next, and which trade-offs matter and stay involved through build, launch, and post-launch measurement.
• Build, maintain, and continuously improve core dashboards and recurring reports used by leadership and teams. Design metrics, definitions, and visualizations that make complex data interpretable and decision-ready.
• Develop a deep understanding of what data exists, where it lives, and how it is collected, transformed, and stored across different platforms. Work closely with Tech to define required events.
• Own data quality end-to-end, including commercial logic and definitions, technical correctness, and logical and technical testing and monitoring.
• Act as the data interface between leadership, marketing, product, engineers, finance, and external data partners—while remaining accountable for analytical delivery. Manage 1–2 freelance Data Engineers / Analysts.

What you'll need

• 5+ years of experience in data analytics within a commercial or product-driven environment.
• Hands-on experience in marketing and growth analytics, with a bias toward action and experimentation. Owned and improved key growth or marketing metrics (e.g. CAC, activation, retention, LTV, ROAS).
• Executive-level storytelling and communication with regular C-level or senior leadership experience.
• Advanced, hands-on SQL skills and the ability to navigate large, complex datasets independently.
• Practical experience using Python for exploration and analysis.
• Strong understanding of attribution logic, funnel analysis, cohort analysis, and their limitations.
• Experience with product and growth analytics tools (e.g. GA4, Firebase, Amplitude, Mixpanel, or similar).
• Comfort connecting commercial data (revenue, subscriptions, payments, billing) with user behavior data.

What they offer

• Impact and purpose around female empowerment and gender equality.
• Female-led company with >90% of team identifying as women+.
• Progressive company culture based on transparency, open feedback, ownership, and collaboration.
• Learning and development budgets and professional business coaching access.
• 26 holidays plus unlimited recharging time.
• Flexible working hours and location with 2.5 months remote working from anywhere.