Location: Geneva, Switzerland
Reporting to the Head, Strategy, Investment and Evidence, the Head, Data, Analytics & Learning is a critical senior management role leading a multidisciplinary team spanning quantitative modelling, measurement, data management and analytics, reporting, evaluation and evidence.
The Head provides strategic leadership for how the Global Fund defines, generates, analyzes and uses evidence across the investment lifecycle, connecting the allocation of resources and modelling of impact with how investments are measured, how programmatic and grant data are collected and analyzed, and how results and performance are reported. The role strengthens the coherence and quality of these interconnected capabilities, reduces fragmentation, and ensures decision-makers have timely, credible and decision-relevant evidence.
Key Responsibilities
1. Organizational Evidence: Set and lead the Global Fund's organizational approach to evidence, analytics and learning, connecting measurement, data, analysis, modelling, performance reporting and evaluation; drive the evolution of evidence capabilities, tools and technologies.
2. Allocation & Modelling: Lead the analytical and modelling capabilities underpinning the allocation of Global Fund resources; oversee modelling, scenario analysis and forward-looking analytics, including for the Investment Case for replenishment cycles.
3. Strategic Measurement: Set the direction for the measurement architecture, including the Modular Framework, Performance Frameworks and the KPI framework, while simplifying reporting and data collection burden.
4. Data & Analytics: Lead the capability to collect, manage, analyze and use programmatic and grant data; build advanced analytical capabilities including data visualization, modelling and appropriate use of AI.
5. Strategic Performance Reporting: Lead strategic performance reporting and provide technical leadership for the Results Report and Investment Case.
6. Evaluation, Learning & Evidence (subject to the Board's approval): Provide strategic oversight of the Evaluation & Learning function as it transitions to an embedded organizational capability, safeguarding impartiality, integrity and uptake of evaluation findings.
7. Organizational Leadership and Capability Development: Build technical depth across the Department, foster a culture of technical excellence, deploy analytical capacity flexibly, and promote digital, data and AI literacy.
Qualifications: Advanced university degree in public health, epidemiology, economics, statistics, data science, international development or a related field (or equivalent combination of academic/professional qualifications and experience). Additional qualification in data science, epidemiology, evaluation, statistics or health economics desirable.
Experience: Demonstrated experience leading multidisciplinary analytical and evidence functions; overseeing complex measurement frameworks and performance indicators; using data, analytics and modelling to inform major resource allocation decisions; leading evaluation and organizational learning; strengthening data and analytical capabilities; advising senior leadership and governance bodies; and leading multidisciplinary teams through managers. Desirable: over 10 years' relevant experience, over 6 years' people management, senior experience in global health or multilateral organizations, knowledge of the Global Fund, and experience shaping responsible AI strategies.
Languages: Excellent English; good working knowledge of French preferred.
About the Global Fund: A partnership designed to accelerate the end of AIDS, tuberculosis and malaria as epidemics, mobilizing and investing more than US$4 billion a year to support programs in more than 100 countries.
Posting End Date 08 November 2026
HOW TO APPLY:
Apply online via the Global Fund Careers recruitment system (Workday) using the Apply link on the job page.
https://theglobalfund.wd1.myworkdayjobs.com/External/job/Geneva/Head--Data--Analytics-and-Learning---GL-F---Defined-Duration-until-December-2029_JR4715-1/apply