Market Modeller

Role Overview
We are looking for someone who is passionate about translating ideas into numbers that enable better decision-making.
You should enjoy analysing commercial value in the context of complex, uncertain and evolving market conditions.
• Build energy market models for Europe using standard tools.
• Perform backcasting to assess model performance.
• Benchmark various available energy market tools.
• Report generation of the model analysis.
Experience
• 3–12 years of relevant experience in energy modelling, optimisation or quantitative analysis within the power sector.
Technical Skills
• Proven expertise in energy system, using quantitative and computational methods.
• Hands-on experience in the modelling, development and deployment of models.
• Strong proficiency in Python for model development, data analysis and automation with the ability to translate technical and business requirements into clean, efficient and maintainable code.
• Strong analytical and problem-solving skills with the ability to research and learn new techniques.
• Experience working with large time-series datasets (prices, load, weather, generation, dispatch).
Communication & Collaboration
• Ability to communicate complex analytical concepts clearly to technical and non-technical stakeholders.
• Strong documentation skills covering models, assumptions and analytical results.
• Collaborative team player with a structured and proactive working style.
Education
• Masters degree from a recognized university (Power Systems, Energy Markets, Applied Mathematics, Economics or related field).
Good to Have Skills
This role is suited for candidates with a strong quantitative inclination who are excited to work on optimization, modelling and market-driven decision-making in energy systems.
• Develop and maintain energy system and market models that capture the interaction between renewable generation, energy storage, demand, grid constraints and electricity markets.
• Validate, stress-test and interpret model outputs to ensure results are technically robust, commercially meaningful and aligned with real-world system behaviour.
• Collaborate with cross-functional teams (engineering, investment and operation) to develop and refine operating and revenue optimisation strategies for renewable and storage assets.
• Translate complex modelling and analytical outputs into clear insights and recommendations for technical and non-technical stakeholders.
• Track and analyse developments across electricity markets in Europe, including day-ahead, real-time, balancing and ancillary service markets to continuously improve modelling assumptions and optimisation approaches.
Tools/software
PLEXOS, PyPSA

Work arrangement
No