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    You are at:Home » Posts » World Bank Group Government Analytics Fellowship 2026 (Fully Funded)
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    World Bank Group Government Analytics Fellowship 2026 (Fully Funded)

    Oluwole OmojofodunBy Oluwole OmojofodunAugust 22, 2025No Comments34 Views
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    World Bank Group Government Analytics Fellowship 2026

    Deadline: September 28, 2025

    The World Bank Group Government Analytics Fellowship 2026 is now open for applications. This prestigious fellowship offers a unique opportunity for mid-level managers and senior analysts in central governments to strengthen their skills in government analytics, drive systemic change, and gain exposure to cutting-edge practices in data-driven governance.


    About the Fellowship

    The fellowship is a 6-month hybrid programme that blends in-person training with in-service mentorship. Selected fellows will design and implement a government analytics project in their home country, guided by experts from leading global institutions.

    The programme includes two weeks of full-time in-person training in Washington, D.C., which will coincide with the World Bank Public Institutions Conference and the Government Analytics course.

    The fellowship is jointly organised by:

    • World Bank Development Economics Vice-Presidency (DEC)
    • Development Impact Group (DECDI)
    • Institutions Global Department
    • Institute for Economic Development
    • University College London (UCL)

    Benefits of the Fellowship

    Successful applicants will enjoy a range of benefits designed to make participation accessible and impactful:

    • Full Funding: Hotel, travel, and subsistence costs will be covered for participants from ODA-eligible countries.
    • Professional Development: Gain advanced skills in government analytics and apply them to real-world projects.
    • Networking: Connect with global leaders, policy professionals, and academics in government analytics.
    • Institutional Impact: Apply insights directly to your organisation to drive measurable improvements in governance.

    Eligibility Criteria

    To qualify for the World Bank Group Government Analytics Fellowship 2026, applicants must meet the following requirements:

    • Be nominated by their organisation (maximum of two fellows per organisation).
    • Be a mid-level manager or senior analyst in central government (or equivalent), with sufficient authority to lead a government analytics project.
    • Have completed tertiary-level coursework in statistics, data science, or other quantitative methods.
    • Demonstrate proficiency in English (both written and spoken).
    • Be available to travel to Washington, D.C. for the in-person training component.

    Application Requirements

    Applicants must submit:

    • A curriculum vitae (CV) not exceeding 3 pages.
    • A 150-word summary explaining how they intend to apply government analytics insights to their organisation.
    • An endorsement letter from their organisation confirming nomination and support.

    Key Dates

    • Application Deadline: September 28, 2025

    How to Apply

    Interested candidates should prepare their application materials and secure organisational endorsement before applying.

    👉 Click here to apply
    👉 Read more about the programme


    The World Bank Group Government Analytics Fellowship 2026 is a transformative opportunity for government professionals seeking to harness the power of data and analytics to improve governance.

    (contact grantsdatabase.org for proposal drafting, refinning and review)

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    Oluwole Omojofodun

    Oluwole Omojofodun is the Proposal Review Team Lead and Publisher at GrantsDatabase.org. With a strong background in grant writing, nonprofit development, and funding strategy, Oluwole oversees the review and refinement of proposals submitted through the platform. His work ensures that applicants are equipped with compelling, funder-ready applications. Passionate about accessibility and impact, he also curates and publishes timely grant opportunities to empower changemakers across sectors.

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