Mama Money

• Design, run, and analyse A/B tests and other experiments across the customer lifecycle; from acquisition and conversion through to retention and reactivation. • Build cohort, funnel, and retention analyses that uncover what's driving customer behaviour and where the biggest opportunities sit. • Lead deep-dive investigations into commercial performance, customer churn, fraud patterns, and product engagement. • Translate ambiguous business questions into structured analytical problems, and the answers into clear recommendations. • Present findings to senior stakeholders in a way that's clear, honest, and decision-ready; not just charts, but conclusions. • Build and maintain self-service dashboards and reports that give teams the data they need, when they need it. • Develop a deep understanding of customer acquisition, conversion, retention, commercial performance, and user experience metrics. • Work alongside the Product and Development teams to shape and deliver on the data roadmap. • Partner with Data Engineers on data quality, modelling, and pipeline reliability, also flagging gaps and helping define what "good" looks like. • Support Customer Success, Commercial, Marketing, and Compliance teams with ad hoc analysis and reporting. • Help create and enforce policies around data governance, quality, and responsible use. • Identify opportunities to improve how we collect, model, and surface data across the business. • Stay close to the customer journey and be curious about how people experience our product and what the data says about it. • Champion experimentation as a core part of how we make decisions.

• Play an active role in researching and implementing new processes, tools, and technologies. • Be involved across the full Software Development Life Cycle (SDLC). • Own test automation for new code, including unit and integration testing. • Help identify and tackle technical debt in existing codebases. • Collaborate across deployment, QA, and support functions. • Champion code quality through thorough peer reviews and knowledge sharing.

• Work closely with Product and Development teams to help deliver components of the data roadmap • Gain a strong understanding of the organisation’s data needs and contribute to building accessible, reliable data solutions • Develop an interest across key business areas such as customer acquisition, conversion, retention, commercial performance, and user experience • Build, refine, and deliver data backlog items in collaboration with the Agile development team • Design, build, and maintain data pipelines, integrations, and transformations to support business reporting and analytics • Support data analysis, dashboard development, and self-service analytics by providing clean, well-structured datasets • Implement data management best practices to ensure data quality, consistency, and reliability • Apply techniques for accurate and complete data collection and validation • Follow secure and efficient procedures for data handling, storage, and processing • Assist colleagues with data access, extracts, and reporting as required • Monitor data systems and pipelines to identify issues, performance bottlenecks, and opportunities for improvement • Troubleshoot data-related issues and support routine maintenance and enhancements • Help ensure data platforms and databases are protected from data loss and security risks • Analyse data trends and provide well-structured datasets to support informed decision-making