Position Description

Data Friendly Space (DFS) is building a roster of experienced Humanitarian Analysts (5+ years) to support analytical outputs, research deliverables, and crisis monitoring across global humanitarian settings. Analysts on the roster may be engaged for situational analysis, monitoring outputs, area-based profiles, thematic products, scenario papers, risk analysis, and ad-hoc analytical assignments, based on expertise and availability.

Roster analysts will work as part of the broader DFS Analysis Team, activated when specific technical needs or surge requirements arise. Work may vary from short-turnaround tasks to longer analytical products, depending on context and assignment scope.

Roles & Responsibilities

Analytical Production

• Lead or contribute to:
  • Situational Analysis Reports
  • Monitoring Reports
  • Area Profiles & Subnational Briefings
  • Scenario Papers
  • Risk Analysis
  • Ad-hoc and Thematic Analytical Products
  • Technical Reviews of Analysis
• Conduct secondary data review, triangulation, and contextual interpretation.
• Synthesize information on needs, access, displacement, response capacity, market shocks, protection concerns, and contextual dynamics.
• Use AI-assisted workflows selectively, maintaining human expertise as the core analytical component.

Surge Response & Crisis Activation

• Serve as part of DFS’s surge/activation team, engaged when sudden-onset crises occur.
• Support analytical delivery when deployments or remote emergency activations take place.
• Contribute to initial situational analysis outputs, area profiles, and urgent analytical products following disasters or escalations.
• Assist in rapid data verification, source scanning, and early crisis framing.

Quality Assurance & Methodological Rigor

• Review and refine outputs for clarity, accuracy, coherence, and methodological robustness.
• Ensure alignment with HNO/HPC processes, JIAF, global clusters, sectoral frameworks, and protection standards.
• Support consistency in storyline, narrative structure, and evidence presentation.

Collaboration & Task Engagement

• Participate in coordination/planning calls for assignments.
• Work closely with DFS colleagues throughout the analysis workflow.
• Provide feedback or light mentorship to volunteer analysts when relevant.
• Deliver tasks within agreed timeframes and maintain communication on availability.

Preferred Profile

• 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.
• Ability to work independently and remotely with strong judgement and writing skills.
• Quantitative/data skills (QGIS, PowerBI, R, Stata, Kobo, advanced Excel) are highly desired.
• Familiarity with AI-assisted analysis is beneficial (training/orientation can be provided).
• Commitment to responsible, evidence-based humanitarian information practice.

Engagement Terms

• Roster-based appointment, analysts are contacted for assignments based on availability, skills, and need.
• Compensation: Determined per assignment/deliverable.
• Location: Fully Remote.
• Duration: Ongoing roster membership with periodic review.

Why Join the DFS Analyst Roster?

• Engage in high-impact humanitarian analysis with real global relevance.
• Work flexibly on diverse products matched to background and expertise.
• Contribute to surge activation and rapid analytical outputs after disasters.
• Gain visibility and recognition for analytical leadership.
• Join an experienced team shaping responsible, human-led analysis enhanced by technology.

About Us

Data Friendly Space (DFS) is a 501(c)(3) non-profit organization based in the United States but with a fully remote team. DFS’ guiding principle is to help social impact organizations just get things done, with specific emphasis on technology, AI, and data analysis. You can learn more about us at datafriendlyspace.org