Reports to: Conservation Impact Manager
Location: Kigali, Rwanda
Country Program/Sector: Africa Protected Areas Management Unit (APAMU)
Capacity: Africa-wide
Position Type: Full-time
Coordinates with: WCS field/site technical teams, WCS Global Conservation Technology, WCS APAMU team
Job Purpose:
The Data Coordinator will support the systematic management and quality of datasets produced by field programs across WCS’ key conservation landscapes and protected area projects in Africa. The position will provide critical support to ensure that data are correct and timely available for decision-making and reporting needs. They will achieve this by working with APAMU Conservation Impact Manager and field-based data managers to ensure that data are managed in accordance with institutional best practices.
Major responsibilities
Data Management & Analysis:
Support the implementation and training of field teams in common data collection and analysis workflows across sites using a suite of software including, but not limited to, SERCA tools (ArcGIS Pro and Enterprise, Kobo ToolBox, SMART, ER, Ecoscope, etc.).
MEL Coordination & Support:
Provide hands-on technical support and capacity building to field teams to improve data practices and use of software and conservation technologies (including GIS, ER, SMART, KoboToolBox, etc).
Internal Qualification RequirementsBachelor’s degree in geospatial analysis, data analytics or similar.
3+ years of experience in data coordination, data management, MEL, or related technical field.
Strong competency in GIS (QGIS and ArcGIS), ESRI products, conservation technology tools; competency in programming languages such as Python and R is an asset.
Experience in using tools for data visualisation (e.g. Tableau, Power BI).
Experience supporting field data collection and management processes (essential), including diverse tools for data collection (KoboToolBox, SMART, EarthRanger).
Strong written and verbal communication skills in English and French; working knowledge of Portugues is an asset.
Demonstrated ability to work independently.
High attention to detail and commitment to data accuracy.
Ability to work collaboratively across teams and countries.
Willingness and ability to travel to field sites, including remote areas with challenging travel conditions to provide training and do data quality assessments.
Desired Skills
Problem-solving: Demonstrated capacity to identify and resolve basic data-related issues.
Attention to Detail: Strong accuracy, consistency, and completeness in all data tasks.
Teamwork: Collaborative approach to working with cross-functional teams.
Continuous Learning: Commitment to expanding technical skills and staying current with MEL and data trends.