Background information about the job or company (e.g., role context, company overview)

This role focuses on health systems evaluation and data analytics within the context of health research.

Responsibilities or duties

Develop and apply probabilistic record linkage methodologies using data from multiple HDSS sites to assess completeness of birth and death registration.

Identify and quantify systematic reporting differences in age-at-death and birth dates in survey and routine data.

Conduct analysis of primary household survey data on birth and death registration to understand factors influencing registration practices.

Generate reproducible scripts and documentation using Python and spatial/statistical packages.

Support geospatially disaggregated analyses to assess implementation strength, equity of access, and quality of care.

Contribute to evaluating the impact of maternal and newborn health initiatives.

Assist in data harmonization and integration across sites using relational databases and web mapping tools

Integrate geospatial analytics and open web mapping tools to support interactive dashboards and decision-support systems.

Apply data mining and statistical inference to assess determinants of inequity and health system performance.

Analysing DHIS2 data to generate actionable insights on health interventions and monitor trends in morbidity and mortality.

Contribute to peer-reviewed manuscripts, technical reports, and policy briefs.

Participate in capacity-building activities, seminars, and collaborative research meetings.

Stay current with emerging methods in health systems science, GIS, and epidemiology.

Qualifications or requirements (e.g., education, skills)

Recognised Postgraduate qualification in MSc in Spatial Data Science, Public Health, Epidemiology, Statistics, or a related field with strong quantitative components.

Proficiency in statistical software (e.g., R, Stata) and GIS tools (e.g., ArcGIS, QGIS).

Strong Python programming skills and experience with web mapping or spatial data pipelines.

Excellent written and verbal communication skills, including scientific writing.

High initiative and willingness to take on new analytical and scientific challenges.

Strong organizational skills and ability to work under tight deadlines.

Ability to work independently and collaboratively across teams.

Experience producing high-quality visualizations and spatial outputs for policy and scientific use.

Experience needed

At least three(3) years working experience in related field, health research.

Experience working with CRVS, HDSS and or DHS, or similar health and demographic datasets.

Any other provided details (e.g., benefits, work environment, team info, or additional notes)

Demonstrated expertise in analytical thinking and statistical methods, with the ability to interpret complex data and generate actionable insights.

• Develop and apply probabilistic record linkage methodologies using data from multiple HDSS sites to assess completeness of birth and death registration.
• Identify and quantify systematic reporting differences in age-at-death and birth dates in survey and routine data.
• Conduct analysis of primary household survey data on birth and death registration to understand factors influencing registration practices.
• Generate reproducible scripts and documentation using Python and spatial/statistical packages.
• Support geospatially disaggregated analyses to assess implementation strength, equity of access, and quality of care.
• Contribute to evaluating the impact of maternal and newborn health initiatives.
• Assist in data harmonization and integration across sites using relational databases and web mapping tools
• Integrate geospatial analytics and open web mapping tools to support interactive dashboards and decision-support systems.
• Apply data mining and statistical inference to assess determinants of inequity and health system performance.
• Analysing DHIS2 data to generate actionable insights on health interventions and monitor trends in morbidity and mortality.
• Contribute to peer-reviewed manuscripts, technical reports, and policy briefs.
• Participate in capacity-building activities, seminars, and collaborative research meetings.
• Stay current with emerging methods in health systems science, GIS, and epidemiology.

• Probabilistic record linkage
• Data analysis
• Python programming
• Spatial/statistical packages
• Geospatial analysis
• Data harmonization
• Web mapping
• Data mining
• Statistical inference
• DHIS2 data analysis
• Scientific writing
• Analytical thinking
• Statistical methods
• Organizational skills
• Collaboration
• Data visualization
• R
• Stata
• ArcGIS
• QGIS

• Recognised Postgraduate qualification in MSc in Spatial Data Science, Public Health, Epidemiology, Statistics, or a related field with strong quantitative components.
• At least three(3) years working experience in related field, health research.
• Experience working with CRVS, HDSS and or DHS, or similar health and demographic datasets.
• Proficiency in statistical software (e.g., R, Stata) and GIS tools (e.g., ArcGIS, QGIS).
• Strong Python programming skills and experience with web mapping or spatial data pipelines.
• Excellent written and verbal communication skills, including scientific writing.
• Demonstrated expertise in analytical thinking and statistical methods, with the ability to interpret complex data and generate actionable insights.
• High initiative and willingness to take on new analytical and scientific challenges.
• Strong organizational skills and ability to work under tight deadlines.
• Ability to work independently and collaboratively across teams.
• Experience producing high-quality visualizations and spatial outputs for policy and scientific use.