Responsibilities

• Lead the end-to-end product analytics workflow, from models and metrics to dashboards and experiments, ensuring insights drive product impact.
• Own and evolve the analytics platform (BigQuery, dbt) in close collaboration with Data Engineering, focusing on reliability, scalability, and high-quality data.
• Define and uphold data reliability standards, including availability, freshness, and incident response practices.
• Set the analytics strategy and roadmap, align priorities with product outcomes, and maintain a transparent, ROI-driven backlog.
• Build a strong experimentation culture by designing tests, guiding PMs and designers, and making results accessible across the company.
• Coach and grow the team in both analytics craft (causal inference, behavioural analytics) and engineering craft (testing, cost and performance optimisation).
• Promote a data-first culture by replacing static reporting with live dashboards that provide consistent views on product adoption, revenue, and operational performance.

Requirements

• Strong technical foundation in analytics, analytics engineering, and statistical analysis.
• Proven experience leading analytics teams and building a data-driven culture.
• Excellent communication and storytelling skills that transform complex data into actionable insights, influencing informed decisions.
• Hands-on experience with business and product analytics, ideally in a SaaS or product-led tech company.
• Solid understanding of data warehousing and modern data stacks.
• Knowledge of key SaaS KPIs such as retention, churn, product adoption, and unit economics.