Responsibilities

• Shape product decisions through data, customer insight, and structured experimentation
• Define and monitor product performance across acquisition, activation, engagement, conversion, retention, transactions, and feature adoption
• Partner with product managers to set success metrics and analytical requirements for roadmap initiatives, new features, and product improvements
• Analyse user journeys, funnels, cohorts, feature usage, and customer segments to identify friction points and opportunities
• Provide analytical support across product discovery, prioritisation, launch readiness, and post‑launch evaluation
• Build and maintain dashboards, alerts, and self‑service reporting tools for consistent product performance visibility
• Design and evaluate A/B tests and structured experiments, quantify impact, interpret results, and recommend next steps
• Develop analytical models including customer lifetime value, churn propensity, conversion pathways, segmentation, and forecasting using SQL and Excel/Power BI; Python or R is a plus
• Present concise, actionable insights that influence product strategy and roadmap decisions while maintaining metric governance and data quality standards

Requirements‍

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Economics, Data Science, or related field; Master’s degree preferred
  3–5 years of experience in product analytics, decision science, growth analytics, or data analysis for digital productsSkills in SQL, Power BI, Python, and R
• Strong SQL skills; proficiency in Excel and Power BI; experience with product analytics platforms such as Mixpanel, Amplitude, or GA4
• Strong understanding of product development, roadmap prioritisation, feature measurement, experimentation, funnels, cohorts, retention, and adoption
• Ability to translate ambiguous product questions into structured analysis, clear conclusions, and practical recommendations
• Self‑driven and detail‑oriented, with strong English communication skills and full Australian work rights

Nice to Have‍

• Python or R for advanced analysis, automation, or predictive modelling
• Experience in gaming, fintech, digital entertainment, marketplaces, subscription services, or other consumer applications
• Experience with event‑based product data, experimentation platforms, or behavioural analytics
• Exposure to multi‑region, high‑growth, regulated, or transaction‑intensive digital products