Overview
The incumbent will support the quality assurance of metadata and microdata submitted to the FAM catalogue for dissemination. They will use technical and analytical skills to conduct statistical risk assessment and apply statistical disclosure control techniques for microdata.
Key Responsibilities
- Review submitted studies and draft DDI compliant metadata
- Assess and decide levels of disclosure risk, and decide and implement appropriate methods for anonymization and organize microdata files received from external providers and datasets received from various FAO technical units and prepare these for publication in the FAM catalogue
- Provide analytical/technical support to internal/external stakeholders on metadata documentation, disclosure risk and anonymization
- Identify relevant datasets in external catalogues and harvest data and metadata and implement their integration into the FAM catalogue
- Review and respond to external users requests for licenced datasets in FAM.
- Manage the internal archive according to the FAO Statistical Standard for Microdata Dissemination
- Support work to develop new procedures to automate routines for identification of relevant citations for publication in FAM.
- Support advocacy for FAM including preparation of articles, newsletters for external audiences, with adherence to FAOSTYLE and corporate communication guidance
- Represent FAO in external webinars promoting FAM catalogue
- Lead project in coordination with relevant units to automate integration of citations to FAM catalogue
- Support ongoing external user consultations to enhance FAM data collections including analysis of results.
Required Experience
- At least 1 year of relevant experience in collecting, manipulating, analysing and disseminating statistical data.
- Extent of knowledge and relevant experience in statistical data management and data dissemination.
- Extent of knowledge of and relevant experience in the use of at least one of the data analysis tools such as R, Python.
- Extent of knowledge and relevant experience in statistical microdata anonymization and dissemination.
- Extent of knowledge and relevant experience in data analysis.
Qualifications
- Advanced university degree from an institution recognized by the International Association of Universities (IAU)/UNESCO in Statistics, Mathematics, Economics, Data Science, Finance or related disciplines. Consultants with bachelor's degree need two additional years of relevant professional experience.
- University degree (or technical degree/certificate) from an institution recognized by the International Association of Universities (IAU)/UNESCO in Statistics, Mathematics, Economics, Data Science, Finance or related disciplines
