Humanitarian Analyst (Roster)

Core responsibilities:

• Lead or contribute to analytical products including situational analysis reports, monitoring reports, area profiles, scenario papers, risk analysis, and ad-hoc thematic products
• Serve as part of surge/activation team for sudden-onset crises, supporting analytical delivery during deployments or remote emergency activations
• Review and refine outputs for clarity, accuracy, coherence, and methodological robustness while ensuring alignment with humanitarian frameworks
• Participate in coordination calls, work closely with DFS colleagues, and deliver tasks within agreed timeframes while maintaining communication on availability

This role creates positive change by providing high-impact humanitarian analysis with real global relevance, contributing to surge activation and rapid analytical outputs after disasters, and helping shape responsible, human-led analysis enhanced by technology.

Required skills and qualifications:

• Strong understanding of humanitarian architecture, sectors, and response frameworks including clusters, HNO/HPC, JIAF, and protection analysis
• Demonstrated experience producing written analysis for UN agencies, INGOs, coordination structures, or research organizations
• Strong ability to synthesize complex information into structured analytical narratives with ability to work independently and remotely
• Quantitative/data skills (QGIS, PowerBI, R, Stata, Kobo, advanced Excel) are highly desired, with familiarity with AI-assisted analysis beneficial

Compensation and engagement terms:

• Compensation: Determined per assignment/deliverable
• Location: Fully Remote
• Duration: Ongoing roster membership with periodic review
• Work flexibly on diverse products matched to background and expertise
• Gain visibility and recognition for analytical leadership
• Join an experienced team

Data Friendly Space (DFS) is a 501(c)(3) non-profit organization based in the United States with a fully remote team that helps social impact organizations just get things done, with specific emphasis on technology, AI, and data analysis.