leading and developing our in-house short-term weather-to-power setup for forecasting wind generation
collaborating on projects to improve our data structure, speed and ML/AI initiatives to choose the right methods, tools and level of complexity to reach business objectives
ensuring reliable, on-time forecast delivery across markets, performance monitoring and incident handling to safeguard quality and performance
turning data into action by developing impactful analytics and visualization tools and creating evaluation frameworks to measure forecast quality and trading outcomes
working in close collaboration with forecast vendors, traders and other stakeholders to extract maximum value from forecast and asset portfolio information.

have bachelor’s degree or higher in mathematics, physics, meteorology, or a related field
have minimum 3-5 years’ experience in a quantitative role, ideally in weather modelling, renewable generation forecasting and short-term trading
have ability to drive performance improvements and innovation in fast-moving, time-sensitive environment
have experience using Python and modern data tools to build (Pandas , Scipy, etc.), validate, and operationalize (CI/CD, Kubernetes, advanced ML) forecasting models on large weather and energy time‑series datasets, working with cloud-based and production-grade data platforms (Azure/AWS).
have strong communication skills, able to explain complex problems clearly, analyse issues and provide comprehensive and actionable solutions.
are fluent in English.

Lead Weather-to-Power Data Scientist

Key skills