About this role
Responsibilities Own and manage the evolution of the commercial data warehouse and analytics ecosystem. Lead the development of advanced dashboards and decision-support tools using Power BI and Azure technologies. Translate complex business challenges into scalable data solutions that deliver measurable commercial value. Act as the Product Owner for the internal business analytics and AI platform, defining the roadmap for new capabilities. Develop and optimize Machine Learning auction prediction models to improve forecasting accuracy and commercial decision-making. Shape the long-term data strategy and operating plan while establishing clear governance and documentation standards. Collaborate with internal stakeholders and external technology partners to bring cutting-edge AI use cases into production. Requirements You possess a Master’s degree or MBA in Data Science , Business Analytics , Artificial Intelligence , Engineering , or a related quantitative field. You have 1 to 3 years proven experience in data analytics , business intelligence , or machine learning , preferably within a data-intensive industry. You bring practical experience using Python and SQL for developing predictive models and advanced analytics solutions. You have a strong understanding of Machine Learning frameworks and data analysis techniques. You possess advanced proficiency in Microsoft Excel and reporting tools such as Power BI . You have a solid understanding of data governance , security, and quality management principles. You're able to bridge the gap between business strategy and technical implementation to maximize value from data. You are proactive and solution-oriented with excellent communication and presentation skills. You are fluent in English Nice to Haves Experience within energy markets, utilities, or financial services. Knowledge of Azure data platform architecture, including security and integration. Knowledge of other languages like Dutch or French would be nice to have Willingness to travel occasionally between international office locations, mainly UK and Germany.