Job Description

As part of its commitment to ecological sustainability across the continent, African Parks (AP) operates a Biodiversity and Science Support (BSS) unit as a support function to assist AP-managed parks and incubation partners through i) improved ecological understanding, ii) strategic conservation planning, iii) technical and analytical guidance, iv) critical decision support, and v) capacity development. Across the AP portfolio, there is a material backlog in ecological data analysis, consolidation, quality assurance, and institutional standardization across monitoring themes and platforms. To address this, AP will recruit a cohort of ten (10) Data Management & Analysis (DMA) interns to support portfolio-level ecological data backlog recovery and to embed standardized, repeatable data workflows across parks and incubator projects.
The DMA interns will report to the Head of BSS and work day-to-day under the guidance of the Data Analysis & Intern Coordinator (DAIC) and Science Interface Manager (SIM), in collaboration with the Business Intelligence (BI) Unit and relevant park-based teams. Each intern will be assigned a thematic stream (based on their relevant skillset, experience and/or interest) and will work across parks to i) identify and consolidate existing datasets, ii) support standardized intake and onboarding into AP monitoring systems, iii) implement data quality assurance and control (including documentation and provenance record practices), and iv) prepare analysis-ready datasets and automated tools to generate basic summary outputs using pre-defined scripts, templates and standard workflows (e.g., R/Python scripts and/or BI templates maintained by BSS/BI). Interns are not expected to develop new analytical pipelines but must be able to run and adapt standard workflows and clearly document and escalate issues as needed.
Thematic streams (10 internship positions):
Applicants must indicate their top three (3) theme preferences and briefly describe their relevant experience/skills for each preference in their application:
1) Observations & Occurrence Records (incl. GBIF alignment): consolidation of occurrence datasets, metadata, taxonomies, and export-readiness for GBIF/Darwin Core-style structures where appropriate.
2) Distance Sampling & Transect Monitoring: collation of transect datasets, effort, and detectability metadata, data quality control, and standardized analysis-ready structures for routine analyses and reporting.
3) Aerial Survey Data: consolidation and harmonization of aerial survey datasets (i.e., AP and partner sources), standardized structures, and comparable summary outputs.
4) Camera Trap Data (incl. VNU-linked workflows where applicable): data consolidation, platform onboarding support (e.g., TrapTagger/WildEye-type workflows), annotation coordination support, and data quality control of camera-trap-derived outputs.
5) Telemetry / Collar & Tracking Data: consolidation and standardization of tracking datasets and effort metrics; quality control; readiness for portfolio-level movement/effort reporting.6) Fire Data & Derived Metrics: compilation of fire datasets (e.g., remote sensing and park records where applicable), standardization, and support to routine fire metrics/annotation.
7) Vegetation, Habitat & Invasive Species: harmonization of habitat/vegetation layers and plot data where present; invasive species tracking structures; standardized spatial products.
8) Connectivity & Landscape Change Inputs: assembling and data quality control of baseline layers and change annotations required to initiate/accelerate connectivity modelling and corridor prioritization.
9) Translocations, Reintroductions & Population Augmentations: consolidation of translocation records, associated monitoring data, and standardized metrics to evaluate outcomes.
10) Species of Special Concern (SoSC) Status & Evidence Base: structured consolidation of SoSC status information and supporting evidence to enable standardized portfolio review and decision support.
Note: depending on portfolio priorities and candidate fit, AP may also allocate additional focus areas within themes (e.g., genetic datasets, human-wildlife conflict/illegal wildlife trade linkages, law enforcement effort integration, and/or research outputs and impact evidence consolidation).
Required qualifications and skills:

• Pursuing or completed a Bachelor's Honours, Master's, or equivalent degree in a relevant discipline (e.g., data science, computer science, statistics, environmental/ecological sciences, GIS, or related fields);
• Demonstrated interest in applied conservation work and the ability to work across multiple datasets and stakeholders in a structured, delivery-focused way;
• Practical capability in data cleaning, organization, and quality control (e.g., spreadsheet competence, reproducible workflows, structured documentation habits);
• A significant and demonstrable level of skill working with analytical and data tools (e.g., R and/or Python, basic SQL exposure advantageous; GIS experience beneficial depending on theme);
• Strong attention to detail, clear written and verbal communication, and ability to manage tasks independently while contributing to a small, collaborative team; and
• Willingness to learn new tools/platforms and follow standardized protocols to deliver consistent portfolio-level outputs.

Beneficial skills:

• Familiarity with ecological monitoring data types relevant to one or more themes (e.g., camera traps, transects, aerial surveys, telemetry, fire/remote sensing, vegetation layers);
• Experience with data standards/interoperability principles (e.g., FAIR/TRUST concepts; Darwin Core/GBIF concepts for occurrence data) where relevant to the theme;
• Experience producing clear summaries/visualizations or supporting dashboard/report outputs (e.g., PowerBI/RShiny/ArcGIS Online-style outputs or equivalent); and
• Speak French and/or Portuguese and have a willingness to travel to remote places.

If you are a driven and motivated professional with a passion for conservation and capacity development, we encourage you to apply for this exciting opportunity.
Please feel free to apply even if you don't have all the required qualifications and skills.
To apply:
Submission of a CV and cover letter to research@africanparks.org by 20th February 2026, including:

• your top three (3) theme preferences (ranked), and
• a summary (2-5 lines each) of your relevant experience/skills for those themes and why you are a good fit.

Skills Required