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CECERN

Energy Data Analyst(m/w/x)

Genf
from CHF 6,372 - 7,004 / month
Full-timeWith Home OfficeManagement
AI/ML
Data Science

Developing Python framework for electricity cost modelling and invoice control at European Organization for Nuclear Research. Python data analysis and quantitative analysis experience required. 30 days paid leave, CERN health insurance.

Requirements

  • Experience developing data analysis or modelling tools in Python
  • Experience handling structured datasets and quantitative analysis
  • Exposure to electrical power systems, energy systems or electricity markets
  • Exposure to machine learning techniques for forecasting (asset)
  • Familiarity with financial or contractual modelling (asset)
  • Understanding of European electricity markets (advantage)
  • 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 for translating technical and market information into quantitative insights
  • Ability to work independently and collaborate effectively in a multidisciplinary technical environment
  • Spoken and written English, with commitment to learn French
  • National of a CERN Member or Associate Member State
  • Professional background in Electrical and/or Computer Engineering or related field
  • Studies focused on Electrical and Computer Engineering, Power Systems Engineering, Computer Engineering, Energy Systems Engineering, Energy Data Analytics or related field
  • Never had a CERN fellow or graduate contract before
  • Valid driving licence

Tasks

  • Develop a Python framework for electricity cost modelling
  • Consolidate existing Excel tools into the Python framework
  • Replace Excel tools for invoice control
  • Replace Excel tools for virtual invoicing
  • Replace Excel tools for cost forecasting
  • Analyze electricity supply contracts
  • Translate pricing mechanisms into financial simulation models
  • Analyze historical operational data for load forecasting
  • Identify electricity consumption patterns
  • Improve forecasting granularity from daily to hourly
  • Integrate real-time data sources into forecasting tools
  • Integrate solar PV production data into analytical tools
  • Explore AI for electricity load forecasting
  • Explore machine learning for electricity load forecasting
  • Explore AI for electricity price forecasting
  • Explore machine learning for electricity price forecasting
  • Monitor European electricity market developments
  • Monitor French electricity market developments
  • Prepare bi-monthly market reports
  • Support procurement with market reports
  • Support risk assessment with market reports
  • Support ISO 50001 energy management activities
  • Prepare documentation for ISO 50001 audits
  • Prepare for ISO 50001 audits
  • Monitor energy performance using data
  • Contribute to commercial follow-up of electricity agreements
  • Contribute to financial follow-up of electricity agreements
  • Contribute to contractual follow-up of electricity agreements
  • Supervise team members

Work Experience

  • 2 - 6 years

Education

  • Master's degree

Languages

  • EnglishNative
  • FrenchBasic

Tools & Technologies

  • Python
  • Machine learning

Benefits

More Vacation Days

  • 30 days paid leave
  • 2 weeks annual closure

Healthcare & Fitness

  • CERN health insurance

Retirement Plans

  • CERN Pension Fund membership

Family Support

  • Family allowances

Additional Allowances

  • Child allowances
  • Infant allowances

Other Benefits

  • Relocation package

Learning & Development

  • On-the-job training
  • Formal training
  • Language classes
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of CERN and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.

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