Data Analyst, Allocation

at  The Global Fund

The Global Fund’s allocation model determines the funding amounts available to eligible countries for each replenishment cycle to fight HIV, TB and malaria. Every three years, the allocation methodology is reviewed to evolve with changing epidemiological and economic contexts and to reflect new data and other information. Work is underway to update the methodology for the 2026-2028 cycle.
The Global Fund is seeking a Data Analyst to join the Allocation Team for the allocation methodology review and implementation to produce final allocations. The Data Analyst would work closely with other team members to prepare high-quality quantitative analysis related to the Global Fund’s allocation model, validate scenario runs of the allocation formula and conduct data quality controls. This role requires using advanced analytical and programming skills.
Key Responsibilities

The key tasks of the Data Analyst will be to:

• Conduct internal validation of the R-code for the allocation formula.
• Conduct quality control of the inputs and outputs of the allocation formula scenarios run by the Specialist, Allocation Team.
• Provide high-quality and timely quantitative analysis on aspects of the allocation methodology.
• Working closely with team members and collaborating with other teams, compile and review programmatic, financial and other relevant grant and country data – and support management of this information on dashboards – for the qualitative adjustments process to finalize the allocations.
• Conduct, as needed, data quality controls on other allocation-related analyses to ensure outputs are accurate and of high quality.
• Support the Allocation Team in implementing the allocation model to produce, verify and communicate final allocation funding amounts.
• Demonstrate a high level of confidentiality and integrity in processing important data

Subject to change by the Executive Director at any time at their sole discretion.
Qualifications

Essential:

• Bachelor’s degree in data science, economics or other quantitative discipline

Experience

Essential:

• At least two years of experience in international development or global health
• Excellent quantitative and analytical skills; at least three years’ experience producing analysis from complex datasets; experience in modelling.
• Sound judgment with ability to apply strategic thinking and high-quality advice based on complex analysis
• Excellent skills in Excel and PowerPoint
• Programming experience in R

Desirable:

• Experience in other programming languages (in particular Python and SQL)

Competencies
Languages:
An excellent knowledge of English and preferably a good working knowledge of French. Knowledge of other languages would be an asset.

Functional Competencies:

• Project Management: Mastery
• Analytical: Mastery
• Communications: Mastery

The Global Fund recruits top-tier talent for our open positions, in support of our mission to end AIDS, tuberculosis and malaria as epidemics.
Explore our vacancies and apply on the
Global Fund Careers
recruitment system.
More information on working at the Global Fund is available on the
Careers
section of our main website.
Job Posting End Date
12 May 202

• Conduct internal validation of the R-code for the allocation formula.
• Conduct quality control of the inputs and outputs of the allocation formula scenarios run by the Specialist, Allocation Team.
• Provide high-quality and timely quantitative analysis on aspects of the allocation methodology.
• Working closely with team members and collaborating with other teams, compile and review programmatic, financial and other relevant grant and country data – and support management of this information on dashboards – for the qualitative adjustments process to finalize the allocations.
• Conduct, as needed, data quality controls on other allocation-related analyses to ensure outputs are accurate and of high quality.
• Support the Allocation Team in implementing the allocation model to produce, verify and communicate final allocation funding amounts.
• Demonstrate a high level of confidentiality and integrity in processing important dat