MEL Intern - INCLUDE Project, Fort Portal

About the role

SNV, a global development partner active in Uganda since more than 35 years, is recruiting a Monitoring, Evaluation and Learning (MEL) intern for its INCLUDE Project in Fort Portal. The project supports 90,000 smallholder farmers across 10 districts through sustainable livestock production and inclusive markets, funded by EKN from April 2024 to March 2029. The MEL function tracks results against the EKN Result Framework and FNS IGG indicators and turns field data into learning. The intern supports the MEL team in collecting, checking and using high-quality data from field activities, working closely with Local Service Providers and Community-Based Facilitators.

Key responsibilities

• Data quality: run scheduled data quality assessments on LogAlto and field records, checking accuracy, completeness, timeliness and consistency, and flagging errors, duplicates and missing fields.
• Field monitoring: monitor activities delivered by LSPs and CBFs, observe sessions, spot-check farmer registration and VLLG records against source documents, and confirm that reported figures match field reality.
• Reporting: compile monitoring data into clean datasets, draft inputs for routine and quarterly reports, and prepare simple tables and charts linked to source files.
• Coaching: coach LSP and CBF teams on data collection tools, mobile data entry and record management, giving practical feedback.
• Data use: support review meetings, pause-and-reflect sessions and feedback to district teams so evidence informs decisions and corrective action.
• Records: keep field MEL records, filing and the data audit trail current and well organised.

Required profile

• Bachelor's degree in Statistics, Computer Science, Information Technology or Agriculture.
• At least two years of experience in MEL activities within development programmes.
• Fluent in English and a relevant regional language for the assigned sub-region.
• Able to work independently in field conditions and travel across assigned districts.

Required skills

• Practical experience with digital data collection platforms such as LogAlto, ODK or KoboToolbox.
• Strong Excel and data management skills.
• Working knowledge of a statistical or visualisation tool (SPSS, Stata, R or Power BI) is an added advantage.

Candidates apply by uploading their CV and a motivation letter in English via the employer's online application system; the deadline is Monday 9 November 2026. Only shortlisted candidates will be contacted.