Role Summary

M31 Research is seeking a highly skilled Technical Expert with strong proficiency in R and QGIS to support a large-scale applied research project involving GIS mapping, digital data collection, and advanced data management. The role focuses on building robust data pipelines, automating data quality checks, supervising spatial mapping workflows, and supporting high-quality analytical outputs from field data.

The successful candidate will work closely with field teams, data managers, and technical partners to ensure accurate data capture, strong quality controls, and reliable spatial and statistical datasets.

Key Responsibilities

• Develop and maintain automated data quality monitoring systems using R.
• Clean, validate, and manage large datasets using R, STATA, and Excel.
• Supervise GIS mapping workflows in QGIS, including polygon digitisation, spatial validation, and surface measurement quality checks.
• Integrate spatial and survey datasets to support analytical modelling and reporting.
• Programme and test digital questionnaires in collaboration with survey teams.
• Monitor field data collection and troubleshoot data, device, and operational issues.
• Produce well-documented datasets, scripts, and technical notes to ensure reproducibility.
• Support enumerator training on digital tools, GPS capture, and data quality standards.
• Provide regular technical reporting on data quality, field progress, and spatial outputs.

Minimum Qualifications and Experience

• Master’s degree in Statistics, Data Science, GIS, Economics, Computer Science, or a related field.
• Strong hands-on experience using R for data management, automation, and quality monitoring.
• Advanced practical experience using QGIS for spatial data processing and analysis.
• Proven experience managing large-scale quantitative survey datasets.
• Solid understanding of data quality assurance frameworks and field monitoring systems.
• Strong analytical skills and attention to detail.
• Excellent written and spoken English.
• Ability to work independently and collaborate effectively with multidisciplinary teams.

Desirable

• Experience integrating GPS and satellite imagery data.
• Familiarity with SurveyCTO, KoboToolbox, or ODK.
• Experience supporting household or infrastructure surveys.

• Develop and maintain automated data quality monitoring systems using R.
• Clean, validate, and manage large datasets using R, STATA, and Excel.
• Supervise GIS mapping workflows in QGIS, including polygon digitisation, spatial validation, and surface measurement quality checks.
• Integrate spatial and survey datasets to support analytical modelling and reporting.
• Programme and test digital questionnaires in collaboration with survey teams.
• Monitor field data collection and troubleshoot data, device, and operational issues.
• Produce well-documented datasets, scripts, and technical notes to ensure reproducibility.
• Support enumerator training on digital tools, GPS capture, and data quality standards.
• Provide regular technical reporting on data quality, field progress, and spatial outputs.

• R
• QGIS
• Data Management
• Automation
• Data Quality Monitoring
• Spatial Data Processing
• Spatial Analysis
• Quantitative Survey Datasets
• Data Quality Assurance
• Field Monitoring Systems
• Analytical Skills
• Attention to Detail
• Written and Spoken English
• Independent Work
• Team Collaboration
• GPS Data Integration
• Satellite Imagery Data Integration
• SurveyCTO
• KoboToolbox
• ODK

• Master’s degree in Statistics, Data Science, GIS, Economics, Computer Science, or a related field.
• Strong hands-on experience using R for data management, automation, and quality monitoring.
• Advanced practical experience using QGIS for spatial data processing and analysis.
• Proven experience managing large-scale quantitative survey datasets.
• Solid understanding of data quality assurance frameworks and field monitoring systems.
• Strong analytical skills and attention to detail.
• Excellent written and spoken English.
• Ability to work independently and collaborate effectively with multidisciplinary teams.