Asset Modelling Engineer

Develop physics-based wind and solar models and the Python software that brings them into daily use in energy trading.

The role

You will develop physics-based models of wind and solar production and build the Python software that puts them into reliable daily operation. Your work will support data validation, pricing, and hedging across our client business.

Over time, you will become the go-to person for asset modelling, taking ownership of model quality, and ensuring that consistent, traceable assumptions underpin our pricing and hedging decisions.

Our asset models are the foundation for how we price renewable energy contracts and estimate the volumes we hedge in the market. We are looking for someone who takes ownership of their models, challenges the status quo and works closely with colleagues to turn theory into practice.

-René Slot, Manager, Pricing

The team

The Pricing team develops and operates the models and analytical infrastructure used to evaluate deals and manage risk across our client business. We focus on making results reliable, traceable and useful for the decisions they support.

You will work alongside a software developer, quantitative developers and pricing analysts, while collaborating closely with colleagues in Forecasting, Portfolio Management and Client Success.

Your responsibilities

• Develop, validate and maintain physics-based wind and solar models, translating weather data and asset characteristics into expected production.
• Validate historical production data and distinguish underlying production potential from the effects of outages, curtailment and trading decisions.
• Build reusable Python components to calculate and store production estimates and expected volumes, ensuring traceability and reproducibility.
• Develop, test, deploy and operate Python models and supporting software, including monitoring, troubleshooting and maintenance.
• Develop and maintain day-ahead and intraday renewable asset hindcasts used in pricing.
• Work with our Forecasting team to incorporate in-house weather data and forecasting methods into our asset models.
• Assess external production indices against our models and document the assumptions behind the analysis.

What we are looking for

You combine expertise in both wind and solar production modelling with strong Python skills and experience taking software into production. You take ownership of model quality and reliability, challenge assumptions and assess whether more complex models add practical value given the uncertainty involved.

We will help you develop your knowledge of pricing, hedging and energy markets. Previous experience in these areas is welcome but not required.

We expect you to have

• A Master’s degree in engineering, physics, renewable energy or a related field.
• Several years of relevant experience in renewable asset modelling, energy yield assessment or a related technical role.
• Hands-on experience with reanalysis data, weather data and measured production time series.
• Solid experience modelling wind production, including turbine power curves and wake effects.
• Solid experience with PV performance modelling and the main drivers of solar production.
• Strong Python skills and experience developing, testing, deploying and operating models or analytical software in production.
• Experience using AI tools in daily coding, analysis or modelling, with a critical approach to reviewing and validating their outputs.
• The ability to communicate technical results clearly and collaborate across technical and commercial teams.

Advantageous experience

• Experience with historical weather forecasts, hindcasts or forecast verification.
• Experience combining physical models with statistical methods to improve production estimates.
• Familiarity with energy markets, PPA pricing or portfolio hedging.

What we offer

• Ownership of our renewable asset modelling capability, with a direct impact on commercial performance.
• The opportunity to combine renewable energy engineering, Python development and quantitative modelling in power markets.
• Hands-on modelling of real wind and solar assets using weather data and measured production.
• Close collaboration with developers, analysts, forecasters and portfolio managers.
• A strong technical environment, with room to shape our models and the analytical services around them.
• Competitive salary and attractive employment terms.

Interested?

If you bring expertise in wind and solar modelling and experience deploying and operating Python software, we would like to hear from you.