MEAL Data Closeout and Evidence Consultant

The consultant will consolidate, clean, verify, and organize the CORN Project's monitoring data and supporting evidence to prepare a complete, accurate, and well-documented data package for internal archiving and handover at project closeout. The role involves data consolidation, verification, evidence compilation, and coordination with project staff and partners.

Responsibilities

• Compile monitoring data from the System and other project data sources.
• Clean and standardize datasets so that formats, indicator definitions, and coding are consistent across the project period.
• Remove duplicate entries and resolve inconsistencies between data sources.
• Organize datasets by indicator, activity, and reporting period for ease of reference.
• Cross-check reported indicator achievements against underlying source documents and field level evidence.
• Verify farmer and beneficiary data, including Village Savings and Loan Association records and business model tracking data, against original records where available.
• Identify and flag discrepancies, gaps, or inconsistencies in the data, and follow up with relevant project staff or partners to resolve them.
• Prepare a data verification report summarizing findings and the actions taken to resolve identified issues.
• Collect, organize, and label supporting evidence, including photographs, attendance records, meeting notes, and documentation from focus group discussions and key informant interviews.
• Compile evidence packages linked to specific indicators and outputs so that achievements can be easily traced and verified.
• Support the finalization of case study documentation and other qualitative evidence materials.
• Ensure all documentation follows Save the Children's file naming and folder structure standards.
• Review datasets to ensure that personally identifiable information is handled in accordance with Save the Children's data protection requirements before archiving.
• Prepare a data dictionary explaining variable names, codes, and definitions used in the consolidated dataset.
• Compile the Final Data Package, including cleaned datasets, tools, supporting documentation, and the data dictionary, ready for handover to Save the Children.
• Support the preparation of a documented handover record confirming what data and evidence have been transferred and archived.
• Upload the Final Data Package to Save the Children's official data storage system, ensuring it is accessible for future reference beyond the consultant's individual files.
• Coordinate with the REALM Specialist, Project Manager, and relevant CORN Project staff to gather outstanding data and evidence.
• Provide data inputs and summaries to support the preparation of the project's final report and any donor facing closeout documentation.
• Escalate any unresolved data quality issues or missing documentation to the REALM Specialist in a timely manner.
• Check and document the resolution status of feedback and complaints recorded through the Feedback Response Mechanism, and escalate any unresolved or sensitive cases to the REALM Specialist and Project Manager.
• Prepare a Data Closure Checklist confirming that all datasets and evidence have been consolidated, verified, and archived, for sign off by the REALM Specialist and Project Manager.
• If requested by the Project Manager, compile summary data on farmer participation, business model achievements, or other relevant indicators for sharing with partners as part of the project's exit process.
• If needed, support to prepare data summaries, key achievement figures, or simple visual materials to support the project's closing ceremony.

Requirements

• Minimum 2 to 4 years of experience in MEAL, data management, or data quality assurance.
• Experience working with monitoring data in agriculture, livelihoods, or rural development programs.
• Strong skills in data handling and cleaning using SharePoints, Excel, Google Sheets, KOBO, or similar tools.
• Experience verifying data against source documents and organizing supporting evidence.
• Good understanding of data protection principles, including the handling of personally identifiable information.
• Strong organizational skills and attention to detail.
• Good communication and coordination skills with project staff and partners.
• Willingness to travel to project locations if required for verification purposes.

Skills

• MEAL
• Data Management
• Data Quality Assurance
• Monitoring Data
• Agriculture Program Monitoring
• Livelihoods Monitoring
• Rural Development Monitoring
• Data Handling
• Data Cleaning
• SharePoint Development
• Excel
• Google Sheets
• Kobo
• Data Verification
• Source Document Verification
• Evidence Compilation
• Data Protection
• Personally Identifiable Information Handling
• Organizational Skills
• Project Coordination

Languages

English