Overview
The Chief, Data and Analytics Branch serves as UNFPA’s Chief Statistician and principal authority on population, health, gender, and development data. The role leads UNFPA’s work across the data value chain to ensure high-quality data underpins policy, advocacy, programming, and results.
Key Responsibilities
- Provide overall vision, strategic direction, and leadership for UNFPA’s data and analytic agenda.
- Lead the implementation of UNFPA’s corporate Data Strategy.
- Oversee the development of standards, methodologies, and global tools.
- Ensure robust data governance, protection, and ethical use.
- Lead UNFPA’s global evidence generation agenda.
- Oversee flagship publications, including substantive contribution to the State of the World Population Report.
- Lead UNFPA’s support to foundational population data systems, including censuses, CRVS, surveys, and administrative data systems.
- Promote innovation in data collection, including digital and hybrid censuses, real-time CRVS systems, integration of administrative data, and application of geospatial technologies.
- Advance the use of AI and machine learning for data processing, estimation, modelling, and predictive analytics.
- Oversee the development and scaling of the Population Data Platform (PDP+).
- Ensure the quality, interoperability, accessibility, and use of data.
- Drive innovation in data dissemination and use.
- Lead strategic engagement with UN agencies, international financial institutions, academia, private sector, and innovation partners.
- Represent UNFPA at high-level global and intergovernmental fora.
- Provide strategic leadership for strengthening national statistical systems and data ecosystems.
- Support countries in adopting modern, digital, and integrated approaches to censuses, CRVS, surveys, and population registers.
- Promote capacity development in data science, AI applications, geospatial analysis, and advanced analytics.
- Foster south–south and triangular cooperation.
- Strengthen internal UNFPA capacity in data literacy, analytics, and responsible use of data and AI.
- Lead resource mobilization for UNFPA’s data and analytics agenda.
- Develop and implement financing strategies to scale investments in data systems, analytics, AI, and geospatial capabilities.
- Engage donors, development banks, and partners to mobilize resources for transformational data systems.
- Oversee the development of high-quality proposals and investment cases.
- Strengthen and position funding mechanisms such as the Population Data Thematic Fund.
- Lead and manage the Data and Analytics Branch, providing strategic direction, performance oversight, and management of human and financial resources.
- Foster a culture of innovation, collaboration, accountability, and excellence.
- Ensure effective collaboration across Programme Division, HQ units, regional offices, and country offices.
- Champion continuous improvement and transformation.
- Perform additional tasks as required by the Division Director or Senior Management.
Required Experience
- Minimum 15 years of progressively responsible experience in public administration and international development.
- At least 8 years at the international level in data, statistics, population, or related fields.
- Recognized technical authority and thought leader in population data, statistics, data systems, or demographic analysis, with up-to-date knowledge of state-of-the-art methodologies and innovations, including AI and geospatial analytics.
- Demonstrated expertise across multiple sectoral data systems, including sexual and reproductive health, gender, humanitarian, migration, and development data systems.
- Proven ability to lead, manage, and inspire high-performing, multidisciplinary teams of experts, delivering measurable and sustained results.
- Strong track record in resource mobilization, programme leadership, and management of complex, large-scale initiatives.
- Extensive experience in global partnerships, inter-agency coordination, and high-level international representation.
- Established and active professional networks within academic, research, and development communities.
- Experience in working in low and middle income countries is highly desirable.
Qualifications
• Advanced university degree in Statistics, Data Science, Demography, Economics, or related field.
