Energy Market Modeller rol in Sydney, NSW

Energy Market Modeller

Enemix are partnering with a leading global energy analytics and forecasting organisation is seeking a highly capable Energy Modeller to join its Sydney‑based forecasting team. The successful candidate will contribute to the development of industry‑leading power market models and revenue forecasts used by developers, investors and operators across renewable energy, storage and distributed energy sectors. This role sits at the intersection of quantitative modelling, energy markets, product development and customer engagement, at the forefront of the energy transition.

Key Responsibilities

• Build and enhance power market, dispatch, and revenue‑forecasting models across multiple regions and asset types.
• Improve model accuracy, scalability and computational performance to support high‑fidelity projections.
• Source, clean and analyse large energy‑market datasets to support modelling and scenario development.
• Convert complex data into actionable insights through structured analysis, visualisation and QA processes.
• Interpret forecast outputs, market design trends and policy changes, producing clear explanatory commentary.
• Present methodologies and results to internal and external stakeholders with varying technical backgrounds.
• Collaborate with product and engineering teams to integrate models and enhance analytical workflows.
• Drive innovation in modelling, automation and tool development to improve forecasting capability.

Experience and Background

• Degree in a quantitative field such as engineering, maths, physics, economics or computer science.
• 3–5 years’ experience in power market or energy‑system analysis, ideally with NEM exposure.
• Proven capability in power system or asset modelling, including forecasting, optimisation and dispatch analysis.
• Strong understanding of renewable technologies, market design and regulatory frameworks.
• Commercial awareness of how forecasts influence investment, development and portfolio decisions.
• Proficiency in Python and scientific computing libraries (NumPy, Pandas, SciPy, scikit‑learn).
• Experience with optimisation tools, linear programming and cloud environments (e.g., AWS).
• Demonstrated ability to apply advanced analytics or AI techniques to enhance modelling workflows.

If you are passionate about energy markets, have a strong analytical mindset, and are eager to contribute to the future of sustainable energy, please apply or send your CV to