Payments Product Analyst, Cleo AI

• A systems thinker: You approach challenges by understanding the interconnected nature of the payments ecosystem, recognising how changes in one area affect the broader system
• Several years of experience performing quantitative analysis in a digital product environment
• Strong SQL skills with the ability to extract insights from complex data sources
• Proven experience contributing to strategic planning, including roadmap development and initiative prioritisation
• A track record of using data to proactively optimise processes and improve performance
• Experience designing and interpreting A/B tests

Desirable

• As a Senior Product Analyst in our Payments Intelligence team, you’ll use data to drive Cleo’s profitability. You’ll play a key role in shaping and prioritising both the strategic and tactical roadmaps that power the development of a world-class payments retry engine
• You’ll define and take ownership of the core metrics that track the efficiency of our payments system. With these metrics in hand, you’ll identify high-impact opportunities to optimise the timing and methods of payment collection - striking the right balance between revenue generation and cost control. This is a rare opportunity to directly influence profitability in a meaningful way
• You’ll also sit within the wider data function here at Cleo; a hotshot chapter of 65 Data Scientists, Product Analysts, and Analytic Engineers with significant industry experience who are at the heart of everything we do at Cleo
• Lead in-depth analysis of the payments retry system to identify high-impact growth opportunities
• Conduct root cause analysis on on unexpected metric movements by examining user behaviour and payments data
• Define and monitor key performance indicators (KPIs) to track the efficiency of our payments platform
• Collaborate cross-functionally with Engineering, Product, and Data Science teams to build a market-leading payments intelligence system
• Design and analyse A/B tests to measure the effectiveness of product changes
• Work with Analytics Engineering to prioritise and contribute to the development of reliable, well-structured data models