Research Data Management Officer at IITA - International Institute of Tropical Agriculture

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.