Revenue Operations Analyst - (all genders) - 100% Homeoffice

We are looking for a Revenue Operations Analyst to improve how we use data across marketing, sales, customer success, product, and billing. Your main responsibility is to understand how our revenue processes perform and why results change. You will define metrics, combine data from different systems, investigate patterns, and test assumptions. Your analyses should lead to measurable improvements. This may involve a better decision, a change to an existing process, or an automation that removes manual work and improves reliability. Reporting and dashboards are part of the role, but they are not the objective. Each analysis should answer a relevant business question and provide a clear basis for the next decision. You will also implement selected solutions, including data models, dashboards, and automations. Analysis remains the main focus. Implementation follows when the expected impact and method of measurement are clear. Previous professional experience is useful but not required. We value analytical judgement, accuracy, technical understanding, and the ability to learn. Tasks Analyse the customer journey from acquisition and conversion to retention and revenue. Define and maintain consistent metrics across marketing, sales, customer success, product, and finance. Extract, combine, clean, and validate data from operational and analytical systems. Investigate changes in customer behaviour, funnels, conversion rates, retention, costs, and revenue. Determine the likely causes of performance changes instead of only describing the result. Review existing reports and identify unreliable metrics, missing data, and conflicting definitions. Develop hypotheses and test them against the available data. Distinguish evidence from assumptions, correlations, and opinions. Estimate the expected impact of proposed changes and define how success will be measured. Prioritise opportunities based on impact, effort, and the reliability of the supporting data. Present findings and recommendations in a form that supports business decisions. Build selected dashboards, data models, automations, and process improvements. Measure implemented changes and assess whether they produced the expected result. Use AI assistants as a daily tool for research, data exploration, coding support, and documentation. Verify AI-generated results against the underlying data and original sources. Document metric definitions, data logic, assumptions, methods, and limitations. Requirements Strong analytical skills and a structured approach to solving problems. A high standard for data quality and reliable results. General programming knowledge and an interest in developing your technical skills. Initial experience with SQL, Python, JavaScript, APIs, spreadsheets, data warehouses, or business intelligence tools is beneficial. A basic understanding of statistics, including the difference between correlation and causation. The ability to examine a problem from different perspectives before reachi