Organisation:
EnGreen

Location:
Remote

Experience:
2-3 years

Deadline:
31 January

23 January, 2026

Energy Data Scientist



Job description

New vacancy

Engreen is offering a position as Data Scientist / Energy Analyst, with a focus on processing, modelling and interpreting energy, environmental and economic data in support of projects related to grid flexibility, hydrogen, biomass, Renewable Energy Communities and decentralised off-grid energy systems. The selected candidate will be responsible for:

  • Managing data flows among production centres and consumers, ensuring users’ protection and security.
  • Performing advanced analysis of consumers’ behaviour through IoT and device monitoring
  • Developing tools, interoperable platforms and AI forecasting models for grid-producers interactions, as well as identifying indicators useful for the technical and economic assessment of projects.
  • Market scouting for innovation in data storage and communication

The position will support the technical and management team in optimising decision-making processes and in defining development strategies. The Data Scientist / Energy Analyst will report directly to the Chief Technical Officer.

Essential skills and qualifications

  • Master’s degree in Energy Engineering, Data Science, Statistics, Mathematics, Physics, Energy Economics or related fields
  • Strong command of data analysis tools (Python, R, SQL) and basic machine learning techniques
  • Ability to process, clean and model complex datasets
  • Knowledge of the main technical and economic drivers of photovoltaic plants and Renewable Energy Communities
  • Experience in energy performance analysis, load profile modelling and simulations of self-consumption/energy sharing
  • Ability to create interactive dashboards (Power BI, Tableau or equivalent)
  • Strong problem-solving skills, critical thinking and ability to summarise complex information
  • At least 2–3 years of experience in similar roles

Desirable skills

  • Knowledge of advanced energy models (e.g. energy optimisation models, PV/BESS load forecasting)
  • Familiarity with energy databases, smart metering and monitoring systems
  • Understanding of energy market logic (wholesale prices, power markets, flexibility)

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