Job Description
DUTIES:
Data Collection and Documentation
- Support project teams in designing and using data collection tools (digital and paper-based).
- Ensure data collection, cleaning, validation, and documentation are carried out in line with IITA/CGIAR standards.
- Support the development and implementation of project Data Management Plans (DMPs).
Data Management and Curation
- Clean, validate, and store datasets generated from project activities.
- Ensure compliance with lITA and donor data management policies, including metadata documentation.
- Curate and archive datasets in institutional repositories, ensuring compliance with the FAIR principles.
- Develop and maintain secure databases and repositories for project data.
- Prepare datasets for submission to lITA repositories, CSpace, and other open data platforms linking them to project outputs.
Data Analysis and Reporting
- Support in the preparation of periodic project reports, dashboards, and visualizations.
- Provide preliminary data analysis to inform program decisions and strategy.
- Assist in generating datasets and evidence for publications, policy briefs, and knowledge products.
Capacity Building and Support
- Build the capacity of project staff and youth beneficiaries in data literacy and management.
- Provide technical support and training to staff and partners on data management practices.
- Provide ongoing technical support in data entry, storage, and retrieval.
Collaboration and Knowledge Sharing
- Liaise with lITA's Data Management and Open Access teams to align with institutional standards.
- Facilitate data sharing within project networks and contribute to open data initiatives where appropriate.
- Apply and promote the use of metadata standards and repositories (e.g., AGROVOC, DataCite, CGSpace).
- Maintain records of datasets generated and shared by the project.
- Perform any other job-related tasks as may be assigned by the supervisor.
Requirements
QUALIFICATION:
- HND/BSc in Computer Science/Engineering, Information Technology, Statistics or any other related course. The ideal candidate must have a minimum of six (6) years’ experience in performing similar role in a well-structured environment.
- Previous experience in agricultural research or development projects is an added advantage.
COMPETENCIES:
The ideal candidate must:
- Demonstrate strong knowledge of data management systems (ODK, KoboToolbox, or similar).
- Possess solid understanding of data curation, metadata standards, and repositories (CKAN, Dataverse, DublinCore, DDI).
- Have experience with digital data cleaning and wrangling tools (e.g., R, Python, Stata, SPSS).
- Show proficiency in data analysis and visualization tools (Excel, SPSS, R, Stata, Python, Power BI).
- Exhibit excellent communication, teamwork, and capacity-building skills.