Head, Data, Analytics and Learning - GL F - Defined Duration until December 2029

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 to strengthen decision-making.
• Drive the evolution of the Global Fund’s evidence capabilities, identifying gaps and opportunities and introducing fit-for-purpose approaches, tools and technologies that improve the quality, timeliness and accessibility of evidence.  

2.    Allocation & Modelling

• Lead the analytical and modelling capabilities underpinning the allocation of Global Fund resources, ensuring methodologies are technically rigorous, transparent and responsive to organizational strategy and the evolving disease and financing context.
• Oversee modelling, scenario analysis and forward-looking analytics to inform strategic choices, resource allocation and investment decisions, including the Global Fund Investment Case for replenishment cycles.
• Ensure allocation and modelling approaches continuously evolve, integrating epidemiological, financial, programmatic and contextual evidence, leveraging artificial intelligence and drawing on expertise from across the Secretariat and external partners.

3.    Strategic Measurement

• Set the strategic direction for the Global Fund’s measurement architecture, ensuring a coherent approach from investment design through grant-level measurement, data collection and organizational reporting.
• Oversee the evolution of the Modular Framework, ensuring it provides a coherent link between what the Global Fund finances, the indicators used to measure performance, and subsequent data collection, analysis and reporting.
• Hold the Strategic Measurement function accountable for fit-for-purpose standards, guidance, systems and tools, ensuring high-quality measurement while driving simplification and reducing unnecessary reporting and data collection burden.

4.    Data & Analytics

• Lead the Global Fund’s capability to collect, manage, analyze and use programmatic and grant data, ensuring decision-makers have timely, reliable and actionable information to inform implementation and investment decisions.
• Strengthen end-to-end use of data across the investment lifecycle, connecting data generated through grants with portfolio analysis, investment decisions, course correction and future cycle design.
• Set direction and build advanced analytical capabilities, including data visualization, modelling and appropriate use of AI and emerging technologies, to generate cross-portfolio insights and respond rapidly to priority analytical needs across GMD and the wider Secretariat.

5.    Strategic Performance Reporting

• Lead the Global Fund’s approach to strategic performance reporting, bringing together performance data, analysis and interpretation to provide a coherent view of progress against organizational strategy and priorities.
• Provide technical leadership and analytical inputs to major organizational reporting, including the Results Report and Investment Case, ensuring narratives, results and forward-looking scenarios are underpinned by robust evidence and analysis.

6.    Evaluation, Learning & Evidence (subject to the Board’s approval)

• Provide strategic oversight of the Global Fund’s Evaluation & Learning function as it transitions from a standalone independent function to an embedded organizational capability, ensuring the new model strengthens the connection between evaluation, data, monitoring and decision-making while maintaining the credibility, objectivity and methodological rigor of evaluation.
• Set strategic direction and priorities for evaluation and learning, ensuring the evaluation portfolio focuses on the questions of greatest strategic importance and generates timely evidence to inform the Global Fund Strategy, policy, investment decisions and organizational improvement.
• Ensure appropriate safeguards for the impartiality and integrity of evaluation within the embedded model, including transparent prioritization, robust methodologies and appropriate governance oversight, so that findings remain credible and able to provide constructive challenge to the organization.
• Strengthen integration between evaluation, monitoring, analytics and other sources of evidence, ensuring these capabilities complement rather than duplicate one another and collectively provide a more comprehensive understanding of what is working, what is not and why.
• Drive stronger organizational uptake of evaluation and learning, holding the function accountable for translating findings into accessible insights and ensuring evidence is systematically brought into strategic, policy and investment discussions and supports course correction where required.
• Ensure effective engagement with governance and external stakeholders on evaluation and learning, maintaining confidence in the quality and integrity of the function.

7.    Organizational Leadership and Capability Development

• Build organizational capability and technical depth across the Department’s disciplines, developing talent and institutionalizing critical expertise to ensure sustainable organizational capability.
• Foster a culture of technical excellence and constructive challenge, encouraging teams to move beyond producing information to interpreting evidence, generating insight and influencing decisions.
• Deploy people and analytical capacity flexibly against priority organizational needs, balancing core deliverables with rapid-response and emerging requirements to maximize the value of available expertise.
• Promote digital, data and AI literacy across the Department, ensuring teams have the skills, mindsets and ways of working needed to use emerging technologies responsibly and effectively.
• Actively contribute to collective leadership across the Division and wider Secretariat, reinforcing a culture grounded in integrity, inclusion, accountability, psychological safety and partnership.

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

Qualifications

Essential:
Advanced university degree in public health, epidemiology, economics, statistics, data science, international development or other relevant field; or a combination of relevant academic/ professional qualifications and experience.

Desirable:
Additional qualification in data science, epidemiology, evaluation, statistics, health economics or other quantitative or evidence-related discipline.

Experience

Essential:

• Demonstrated experience leading multidisciplinary analytical and evidence functions, integrating different forms of quantitative and qualitative evidence to support strategic, investment and management decision-making.
• Significant experience overseeing complex measurement frameworks, including development and use of indicators and performance frameworks to assess organizational, portfolio and/or programmatic performance.
• Demonstrated experience using data, analytics and modelling to inform major resource allocation and investment decisions, including scenario analysis and interpretation of complex epidemiological, financial and programmatic evidence.
• Significant experience leading or overseeing evaluation and organizational learning, including ensuring methodological rigor and credibility while translating evidence into actionable insights and organizational improvement.
• Demonstrated experience strengthening organizational data and analytical capabilities, including improving data quality, governance, accessibility, visualization and the effective use of technology and emerging analytical approaches.
• Proven experience advising senior leadership and governance bodies on complex evidence and performance issues, translating technical analysis into clear insights, choices and recommendations for non-technical audiences.
• Proven experience leading multidisciplinary teams and managing through managers, building technical capability and fostering collaboration across organizational boundaries.
• Track record in engaging senior stakeholders, managing sensitivities and securing alignment on strategic issues.

Desirable:

• Over 10 years’ relevant professional experience
•  Senior-level experience in data, analytics, measurement, evaluation and/or strategic performance, ideally within global health, international development or a multilateral organization.
• Over 6 years of people management experience
• Demonstrated knowledge of the Global Fund and its partnership model, governance, policies and processes
• Experience with resource allocation methodologies, epidemiological or impact modelling, and portfolio-level analytics.
• Experience shaping responsible AI, automation or digital analytics strategies in a public health, international development, multilateral environment.

Competencies

Languages:

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

Functional Competencies:

• Analytical (Expert)
• Business (Expert))
• Communications (Expert))
• Geopolitical awareness (Mastery)
• Global/Public Health (Mastery)
• Disease Knowledge (Mastery)
• Human Rights/Gender/ Key Populations (Mastery)
• IT (Mastery)
• Project Management (Mastery)
• Country Context (Mastery)
• Risk (Mastery)
  

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