JOB SUMMARY: The role of the Assistant, Monitoring, Evaluation, Accountability, and Learning (MEAL) is to support the Officer, MEAL in the implementation of the MEAL work plan and contribute to achieving and improving the quality of the program/project. The Assistant, MEAL will follow-up progress and collect data on the effectiveness of planned interventions by collecting and supporting with the data analysis. The MEAL Assistant plays an important role in carrying out MEAL activities in the field, including field monitoring and verification, baseline and endline assessments, needs assessment and surveys.
To perform this job successfully, an individual must be able to perform each essential function with or without reasonable accommodation:
MAIN TASKS AND RESPONSIBILITIES
IMC’s policies, guidelines, and procedures
- Actively promote Prevention of Sexual Exploitation and Abuse (PSEA) standards within IMC and amongst its beneficiaries.
- Contribute to the creation of a positive image and overall credibility of the organization, notably through the application of the Code of Conduct, ethics, values, and standpoint with regards to internal and external actors.
MEAL system
- Use data collection tools to gather qualitative and quantitative data at different levels (facility and community).
- Support MEAL department in development of databases for all programs by using available technologies.
- Implement the basic monitoring and evaluation concepts and system in accordance with the purpose of MEAL activities.
- Implement field level MEAL activities according to the MEAL work plan and support M&E activities, such as post distribution monitoring, data quality audits, surveys/assessments, operational research, etc.
- Perform data entry into electronic databases as needed.
- Support in the implementation of gender analyses and gender assessments as required, including data collection and data analysis.
- Support in the translation of tools and data.
- Ensure tools and systems are in place for learning and decision making on the needs of vulnerable groups, including disaggregation of all data by sex, age, disability status, and others.
Data quality management
- Conduct on-site routine data quality audits at different field site/office-levels.
Sampling
- Implement probability and non-probability sampling techniques as and when appropriate after consulting with manager.
Qualitative and quantitative techniques 
