Energy Data Analyst (HSE-ENV-EC-2026-57-GRAP)

About

The Energy Data Analyst will contribute to the digital transformation of CERN's electricity cost modelling and load forecasting framework within the Energy & Climate Action section of the Environmental Protection group.

The role focuses on migrating legacy financial and forecasting tools to a structured Python-based analytical platform, enhancing forecasting granularity and potentially exploring AI-driven approaches for electricity load and price forecasting.

The position also involves monitoring electricity market developments and supporting CERN's ISO 50001 energy management activities.

Responsibilities

• Develop and consolidate a Python-based framework for electricity cost modelling, harmonising and replacing existing Excel tools used for invoice control, virtual invoicing and cost forecasting.
• Analyse electricity supply contracts and translate pricing mechanisms into structured financial simulation models.
• Contribute to CERN's load forecasting activities by analysing historical operational data, identifying consumption patterns and improving forecasting granularity from daily to hourly resolution.
• Integrate real-time data sources, including solar PV production, into forecasting and analytical tools.
• Explore and test AI and machine learning approaches for electricity load and price forecasting.
• Monitor developments in European and French electricity markets and prepare bi‑monthly reports supporting procurement and risk assessment.
• Support ISO 50001 energy management activities, including documentation, audit preparation and data‑driven performance monitoring.
• Contribute to cross‑functional activities related to the commercial, financial and contractual follow‑up of the various electricity supply agreements.
• This role includes team supervision responsibilities.

Profile

• Experience developing data analysis or modelling tools in Python (e.g. time‑series analysis, statistical modelling or optimisation) in either an academic or industrial environment.
• Experience handling structured datasets and performing quantitative analysis.
• Exposure to electrical power systems, energy systems or electricity markets through studies, internships or research projects.
• Exposure to machine learning techniques applied to forecasting problems is a strong asset.
• Familiarity with financial or contractual modelling is an asset.
• Understanding of European electricity markets is an advantage.

Skills

• Strong programming skills in Python for data processing, modelling and visualisation.
• Solid understanding of electrical power systems fundamentals.
• Ability to design structured, maintainable and scalable analytical tools.
• Good understanding of time‑series analysis and statistical modelling principles.
• Analytical mindset with the ability to translate complex technical and market information into quantitative insights.
• Ability to work independently while collaborating effectively in a multidisciplinary technical environment.
• Spoken and written English, with a commitment to learn French.

Eligibility Criteria

• You are a national of a CERN Member or Associate Member State.
• You have a professional background in Electrical and/or Computer Engineering (or a related field).
• Your studies focused on Electrical and Computer Engineering, Power Systems Engineering, Computer Engineering, Energy Systems Engineering, Energy Data Analytics or a closely related field and have either:
  • a Master's degree with 2 to 6 years of post‑graduation professional experience; or
  • a PhD with no more than 3 years of post‑graduation professional experience.
• You have never had a CERN fellow or graduate contract before.