Company Description
SNV is a not-for-profit international development organization that applies practical know-how to make a lasting difference in the lives of people living in poverty. We use our extensive and long-term in-country presence to apply and adapt our top-notch expertise in agriculture, energy, and WASH to local contexts. SNV has over 1250 staff in more than 25 countries in Asia, Africa, and Latin America. We are proud to be a not-for-profit organization that uses project financing to implement our mission. This requires us to work efficiently and to invest in operational excellence. In its new Strategic Plan period (2019 – 2022), SNV will more explicitly aim for systems change during project preparation and implementation - by strengthening institutions and kick-starting markets that help many more to escape poverty beyond our projects. We will continue to position ourselves as a premium organization and invest in making knowledge flow to and from the frontline.
For more information on SNV, visit our website: www.snv.org
About the project Transformative Land Investment (TLI)
TLI Project aims to contribute to a more responsible land-based investments contributing to a more sustainable food systems, with gender-sensitive and socially inclusive improvements in land tenure security, livelihoods, resilience, and ecosystem health, through capacity strengthening and catalyzing partnerships. in its quest to contribute to Responsible Land Based Investments, TLI will work with big land-based investments to capacitate their interventions in making their investments responsible.
Interested and Eligible parties are invited to send in the following documents
Resume: showing qualification (as individual consultants or firms or associations) including individual experts CVs for firms or institutes. The CVs should clearly show relevant/related works done
Reference: reference/acknowledgement letters from clients on similar works done
Letter of Intent: A letter indicating interest to work with the project on their expertise based on specific ToRs