Overview
The Data Analyst Specialist will strengthen results-based management in planning and implementation related to the UNFPA–UNICEF Joint Programme on the Elimination of Female Genital Mutilation.
Key Responsibilities
- Generate FGM risk incidence and attitudinal risk incidence from DHIS, MICS, and other surveys for 18 countries.
- Generate Subnational Administrative Estimates (SAE) of FGM prevalence from DHIS, MICS, and other surveys for 18 countries.
- Feed the FGM social media database from 2008 to 2025 into UNFPA’s Demographic Intelligence from Open Sources (DIOS) platform.
- Link geospatial Joint Programme (JP) programmatic data with the above data, FGM social media (DIOS), and Google embeddings.
- Pilot test social norm indicators in existing surveillance/health information systems using Open Data Kit (ODK) or Kobo Toolbox.
- Pilot test generating FGM data among small or hidden populations using a respondent-driven sampling approach.
Required Experience
- 3 years of relevant experience.
- A technical professional with a strong interdisciplinary background in data science, with extensive experience in statistical analysis using large datasets.
- Hands-on expertise in geospatial and artificial intelligence (AI)-driven analysis, applying tools such as QGIS, Python, R, small area estimation models, and large language models to generate epidemiological insights across complex, multi-country settings is preferred.
- Demonstrated experience in large-scale data management, including the design and use of data entry systems such as the District Health Information Software 2 (DHIS2 ) and Structured Query Language (SQL).
- Experience in the design and operationalization of indicator measurement drawing on survey methodology, respondent-driven sampling, and field surveillance systems, using digital data collection tools including Open Data Kit (ODK) and Kobo Toolbox.
Qualifications
Master's degree in statistics or biostatistics or epidemiology or Public Health with special focus on quantitative/biostatistics track. Public health applications in Computer Science will be an added advantage.