Data analysis and visualizations for Nature for Development team

Tags: UNDP Environment
  • Added Date: Wednesday, 29 October 2025
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Mission and objectives UNDPโ€™s Global Programme on Nature for Development brings together three different initiatives under one program โ€“ the Equator Initiative, the National Biodiversity Initiative, and the Global Forest Initiative โ€“ in order to identify, foster, showcase and celebrate nature-based solutions that help achieve the 2030 Agenda for Sustainable Development at local, national and international levels. The work of the Global Programme on Nature for Development contributes to UNDPโ€™s Strategic Plan 2014-2017 by charting sustainable development pathways through the conservation, restoration and sustainable management of biodiversity and ecosystems; and by promoting inclusive and effective democratic governance in the area of natural resources.

ContextThe National Biodiversity Strategies and Action Plan (NBSAP) Accelerator Partnership (AP) is a country-led global initiative to support accelerated NBSAP implementation and strengthen countriesโ€™ ambition and action to halt and reverse biodiversity loss and put nature on a path to recovery for the benefit of people and planet by 2030. The NBSAP Accelerator Partnership developed and disseminated two surveys and one expression of interest through the Convention on Biological Diversity in 2023. The analysis of these surveys will feed and inform a briefing note that the Accelerator is developing which seeks to frame country identified needs and capacity gaps to implement their NBSAP and achieve the GBF by 2030.

Task DescriptionUNDP is looking for one online volunteer to provide support in data analysis and visualization for a briefing note that the NBSAP Accelerator Partnership is developing. The results of the analysis will be featured in the briefing note and promoted at the 2024 United Nations Environment Assembly. The online volunteer will be provided with the data sets and will be asked to conduct data analysis and visualizations on the three data sets.

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