Fundraising Data Analyst
Pubblicato il 10-10-2026 - WFP in Pordenone
Organizational contextThe World Food Programme (WFP) is the world's largest humanitarian organization, dedicated to saving lives and building a pathway to peace and prosperity. WFP assists millions globally, working in 83 countries to combat hunger and malnutrition through emergency response and long-term development programs. The organization is committed to a data-first, evidence-driven approach to its operations and fundraising.
Job purposeThe Fundraising Data Analyst will play a crucial role in supporting WFP's individual giving teams by providing essential data insights, expertise, and tools. This position is vital for ensuring the effectiveness of fundraising efforts and enhancing the supporter experience. The analyst will be responsible for creating and maintaining reporting dashboards, conducting internal analysis projects, and managing project needs from the Individual Giving team. They will also collaborate with tech teams to improve data warehousing, offer technical and analytical support, and explore advanced AI applications for deeper insights and automation.
This role requires a proactive approach to understanding supporter motivations, market trends, and translating data into actionable strategies to drive WFP's fundraising success.
ResponsibilitiesThe primary responsibilities involve creating and maintaining reporting dashboards using Tableau Server, and supporting internal analysis projects by liaising with key stakeholders. A significant part of the role includes project managing the needs of the Individual Giving team, prioritizing projects, understanding stakeholder requirements, and providing progress updates. This also entails working with technical teams to enhance BI warehouse datasets and offering technical and analytical support to fundraising products. A key focus is on incorporating advanced AI for analysis, aiming to automate routine tasks and uncover deep insights. The role requires staying current with industry trends in analysis and r