vom 28.08.2026
We are looking for a Revenue Operations Analyst to support the improvement of how we use data across marketing, sales, customer success, product, and billing.
Tasks: Analyse the customer journey across acquisition, conversion, retention, and revenue performance. Define, refine, 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 trends. Identify the likely drivers behind performance changes rather than only describing outcomes. Review existing reports and identify unreliable metrics, data gaps, and inconsistent definitions. Develop hypotheses and validate them using available data and analytical methods. Separate evidence-based insights from assumptions, correlations, and opinions. Estimate the potential impact of proposed improvements and define suitable success metrics. Prioritise opportunities based on expected impact, effort, and confidence in the underlying data. Present findings and recommendations in a clear format that supports business decisions. Support the development of selected dashboards, data models, automations, and process improvements. Evaluate implemented changes and measure whether they achieved the expected impact. Use AI-assisted tools where appropriate for research, data exploration, coding support, and documentation. Validate AI-generated outputs against underlying data and original sources. Document metric definitions, data logic, assumptions, analytical methods, and limitations.
Requirements: Strong analytical skills and a structured approach to solving complex problems. A high standard for data quality and a focus on producing reliable results.General programming knowledge and the motivation to continuously develop technical skills. Initial experience with tools and technologies such as SQL, Python, JavaScript, APIs, spreadsheets, data warehouses, or business intelligence platforms is beneficial. A basic understanding of statistics, including the distinction between correlation and causation.The ability to analyse problems from multiple perspectives before drawing conclusions. An interest in using AI-assisted tools as part of analytical and technical workflows. The ability to critically evaluate and validate AI-generated results. Strong communication skills and the ability to explain complex findings in a clear and understandable way. The curiosity and motivation to learn new tools, systems, and business areas. The discipline to follow an analysis through to a sufficiently reliable and actionable conclusion.
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