Overview
The intern will support ongoing work related to data analytics and digital tools, including contributions to a foresight platform and related analytical workflows.
Key Responsibilities
- Assisting with data management, and structured analysis using tools such as Python, or similar.
- Supporting development and improvement of data visualizations and dashboards.
- Assisting in organizing and integrating datasets for analytical use.
- Supporting testing and refinement of platform features, including data and user interface components.
- Assist in conducting research on emerging AI trends, tools, and best practices relevant to Foresight.
- Contributing to exploratory work on AI-enabled approaches (e.g. trend analysis, text analysis, or signal detection), under supervision.
- Conducting research on data sources, analytical methods, and emerging technologies.
- Supporting documentation of data processes, workflows, and methodologies.
- Assisting in preparation of technical inputs to reports, presentations, and briefs.
Required Experience
Applicants to the UN Internship Programme are not required to have professional work experience. However, a field of study that is closely related to the type of internship that you are applying for is required. Applicants must be a student in the final year of the first university degree (bachelor or equivalent), master’s or Ph.D. Programme or equivalent, or have completed a Bachelor’s, master’s or PH.D. Programme, preferably in the area of a relevant domain and experience with AI tools or technologies.
Qualifications
- a) Be enrolled in a graduate school Programme (second university degree or equivalent, or higher).
- b) Be enrolled in the final academic year of a first university degree program (minimum bachelor's level or equivalent).
- c) Have graduated with a university degree and, if selected, must commence the internship within one year of graduation.
- Be computer literate in standard software applications.
- Field of study: web development, computer science, information technology, data science or another related field is required.
- Knowledge of data science analysis tools (e.g. Python, or similar) is required.
- Understanding basic concepts in data analytics and statistics is required.
