Job Description


The Organisation for Economic Co-operation and Development (OECD) is an international organisation comprised of 38 member countries, that works to build better policies for better lives. Our mission is to promote policies that will improve the economic and social well-being of people around the world.  Together with governments, policy makers and citizens, we work on establishing evidence-based international standards, and finding solutions to a range of social, economic and environmental challenges. From improving economic performance and creating jobs to fostering strong education and fighting international tax evasion, we provide a unique forum and knowledge hub for data and Analysis, exchange of experiences, best-practice sharing, and advice on public policies and international standard-setting.

The International Energy Agency (IEA) is an intergovernmental organisation committed to advancing security of energy supply, economic growth and environmental sustainability through energy policy co-operation. The IEA operates as an autonomous body within the framework of the Organisation for Economic Co-operation and Development. Both the IEA and the OECD seek opportunities to work with an increasing number of non-members of growing importance to the world economy (countries beyond IEA). The Agency aims to foster the contribution of the Energy Sector to economic development and environmental sustainability across the globe.

The IEA seeks motivated Data Managers for two key divisions within the Agency:

  • The IEA Energy Data Centre (EDC) is responsible for collecting and disseminating a broad portfolio of energy statistics to monitor developments in the energy sector and to provide to its Members and beyond a sound basis for policy decisions.
  • The Sustainable Technology Office (STO) is responsible to deliver scenarios using IEA’s Global Energy and Climate Model, such as those of the World Energy Outlook and Energy Technology Perspectives.

    EDC and STO are seeking Data Managers for the collection, compilation, verification, research and dissemination of energy data, as well as to utilise this data in IEA modelling tools. The chosen candidates will participate in the energy data-related activities that underpin the Agency’s work on global energy challenges, including that on Clean Energy transitions modelling. These activities include, but are not limited to, energy security (including the IEA Emergency Data System), energy markets and prices, energy efficiency and innovation, GHG emissions, as well as specific research tasks associated with the development of IEA publications and data products supporting the IEA focus on clean energy transitions. In addition, Data Managers are expected to play a central role in the IEA’s modernization strategy, with increased emphasis on the exploitation of new data sources and the use of relevant methods and tools. 

    Main Responsibilities

    Data Collection, validation and development

    • Collect, review, input, and validate data received from various sources. Continually improve methods to ensure data quality and international comparability.
    • Develop and implement robust methods for the estimation of missing values if and when necessary.
    • Develop derived indicators and metrics to support tracking of energy market developments globally.
    • Identify new data sources (e.g. commercial, administrative, etc…) and collection methods (e.g. web-scraping) to track relevant areas of national and global energy systems.
    • Maintain appropriate documentation on data series, draft methodological and technical notes on statistics for various releases and publications.
    • Keep abreast of the work of other international and national organisations (e.g. UN, Eurostat, the World Bank, etc.) on related topics, and collaborate as needed.
    • Oversee and guide the work of more junior staff for the data collection, validation and dissemination tasks.

      Database management, support, dissemination and analysis

      • Manage, maintain and develop statistical databases exploiting new software developments to improve the efficiency of working methods covering a range of statistical areas.
      • Ensure the integration of new data sets into the existing data infrastructure including those developed from micro-data and through the use of data science methods.
      • Provide guidance to internal and external users on data preparation and interpretation for use in empirical analysis and modelling, and address the changing needs of users by contributing to statistical development work.
      • Oversee, guide, and lead in the production of statistical and analytical publications, reports and data products, via the preparation of visuals and text accompanying the statistical information.
      • As needed, deliver presentations and training in different settings, whether classroom or online, including to experts worldwide.
      • Train new recruits to the energy data center on statistical methodologies and processes.

        Candidate’s profile

        Academic Background

        • A university degree in fields relevant for energy data, i.e. statistics, data science, economics, mathematics, Computer Science, information technology, engineering, physics, environmental studies. A postgraduate degree in one of these fields would be an advantage.

          Professional Background

          • Proven experience in the production and/or use of data or statistics gained in the private sector, university, public research institute, national Administration or or international organisation.
          • General knowledge of statistical concepts and applied Data Analysis techniques.
          • Demonstrated experience in quantitative analysis and/or knowledge in the energy field would be an advantage.
          • Strong communication skills, including capacity to present technical content to non-technical audiences.
          • Demonstrated experience with project management would be an advantage.


            • Experience performing Data Processing and analysis using programming languages such as Python, R, and Matlab.
            • Experience in developing visuals with business intelligence softwares, such as but not limited to Power BI, Tableau, Looker, or Plotly/Dash would be considered a significant advantage.
            • Experience in using Microsoft Office software, especially Excel and Visual Basic.  
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