Advocacy, Reporting and Data Intern at UN-Habitat

Duties and Responsibilities

Stakeholder Database Management and Updating

• Maintain and regularly update the stakeholder database with new registrations, consultation records, and stakeholder contacts

Data Cleaning and Consolidation

• Apply agreed data cleaning rules to ensure accuracy, consistency, and integrity of the dataset
• Conduct regular data quality checks and validation

Data Analysis and Reporting Support

• Prepare and maintain analysis-ready datasets for reporting and stakeholder engagement activities
• Apply appropriate AI Tools to enhance data analysis, automate processes, and improve reporting outputs.
• Support the generation of summary statistics as requested and develop analytical outputs on different applications (e.g. Excel, Canva, PowerBI, SPSS) 4)

Global Advocacy and campaigns

• Develop compelling advocacy materials, including articles, blog posts, social posts, and newsletters, to effectively communicate key messages on adequate housing and sustainable urban development.
• Collaborate with team members to create visually engaging content, to amplify advocacy efforts.
• Support the team on planning, organization and execution of advocacy events, WUF sessions, and campaigns aimed at raising awareness and mobilizing support for housing and urban initiatives.
• Support logistics and manage communications and ensure seamless execution of events both in-person and virtually.

Coordination of the UN-Habitat Strategic Plan Subprogramme

• Maintain and regularly update the monitoring and reporting database of Subprogramme 4 with inputs from the UN-Habitat Focal Points; Support the collaboration networks and database of Focal Points.
• Support the Subprogramme 4 Coordinator in drafting the progress reports and related presentations for the Director of GKAD, the UN-Habitat executive management group and for review meetings by governing bodies of UN-Habitat.

Qualifications/special skills

Applicants must at the time of application, meet one of the following requirements:

• Be enrolled in a graduate school programme (second university degree or equivalent, or higher),
• Be enrolled in the final academic year of a first university degree program (minimum Bachelor's level or equivalent),
• Have graduated with Bachelor's degree, Masters, PhD or equivalent.
• Be computer literate in standard software applications (Microsoft Office Suite).
• Have demonstrated a keen interest in the work of the United Nations and have a personal commitment to the ideals of the Charter.
• Have a demonstrated ability to successfully interact with individuals of different cultural backgrounds and beliefs, which includes a willingness to try and understand and be tolerant of differing opinions and views. Preferred areas of study: Bachelor’s degree in Data Science / Statistics, Economics, Information Management / Information Systems, Communications, Public Relations, Business Administration, Urban Studies / Development Studies or related field is required.
• 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. Do you meet any of the above criteria? If yes, please indicate which one and attach proof to the application.
• Please note that you will have to provide an official certificate at a later stage. Proficiency in Microsoft Excel for data management and analysis is required.
• Please explain how you meet this criterion, including examples of how you have used Excel to clean, organize, or analyse datasets (e.g. use of formulas, filtering, deduplication, or pivot tables).
• Experience in data cleaning, consolidation, and managing large datasets is required.
• Please describe your experience handling datasets with duplicate or inconsistent entries, including the approach you used to identify, clean, and consolidate data.