Programme Management Officer, P3

• Organize and conduct collection, evaluation, and dissemination of statistical data on Economy-Wide Material Flow Accounts (EW-MFA) and related data.
• Develop and improve statistical models and projections to support EW-MFA analysis.
• Manage EW-MFA and other statistical databases.
• Provide training and technical support to national statistical offices and ministries on data collection and practices related to EW-MFA.
• Offer feedback and advice on data published in UNEP's global databases and tools.
• Prepare written outputs including background papers, reports, and publications.
• Participate in developing or revising standards on statistical concepts and classifications related to sustainable material use.
• Organize and take part in seminars, working groups, and expert meetings as a technical resource.
• Conduct outreach activities on EW-MFA and related data and tools.
• Guide, train, and supervise junior staff.
• Coordinate budget and funding activities including programme preparation, reports, and financial statements.
• Collect and analyse data to identify trends and provide insights using data visualisation methods.

• Advanced university degree (Master's or equivalent) in statistics, mathematics, or economics is required; a first-level degree with two additional years of experience may be accepted.
• At least five years of progressively responsible experience in statistical data collection, analysis, and dissemination, ideally related to material flow analysis or sustainable development.
• Experience in analysing and interpreting data and preparing briefs for diverse audiences.
• Proven experience in modelling sustainable consumption, production, and circular economy scenarios.
• Experience in an international organisation is desirable.
• Two or more years of experience in data analytics or related fields is desirable.
• Proficiency in English at UN Level III is required; French at UN Level II is desirable.
• Successful completion of degree or non-degree programmes in data analytics, business analytics, or data science is desirable.

Apply on the employer's application page. The closing date for applications is Sunday, 29 November 2026.