What you'll do
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.
Your 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.
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Your 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.
- Your studies focused on Electrical and/or Computer Engineering.
Your 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.
Employment conditions
- A valid driving licence.
Global Benefits at CERN
Let's get you ready
Be sure to meet the eligibility criteria
- You are a national of a CERN Member State or Associate Member State. Currently, we cannot consider applications from Pakistani and Lithuanian nationals for positions with a 2026 start date, as the ceiling defined under Article II.5 of the Associate Membership Agreement has been reached.
- By the application deadline, you have a master’s degree with 2 to 6 years of professional experience since graduation or a PhD with a maximum of 3 years of professional experience since graduation. You are not eligible with only a bachelor’s degree.
- You have never had a CERN fellow or graduate contract before.
- Please pay attention to the additional criteria and requirements for this specific position and mentioned above.
You will need these documents to complete your application
- Your CV (English or French)
- A copy of your most relevant diploma or a certificate of achievement from your school (if you don't yet have your paper diploma)
- Any document you consider relevant to your application