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Statistician/Data Analyst – microdata

Rome (Italy)

  • Organization: FAO - Food and Agriculture Organization of the United Nations
  • Location: Rome (Italy)
  • Grade: Consultant - Contractors Agreement - Consultancy
  • Occupational Groups:
    • Statistics
    • Information Technology and Computer Science
    • Scientist and Researcher
  • Closing Date: 2021-06-14

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IMPORTANT NOTICE: Please note that Closure Date and Time displayed above are based on date and time settings of your personal device

  • FAO is committed to achieving workforce diversity in terms of gender, nationality, background, and culture
  • Qualified female applicants, qualified nationals of non-and under-represented member nations, and person with disabilities are encouraged to apply
  • Everyone who works for FAO is required to adhere to the highest standards of integrity and professional conduct and to uphold our values. FAO has a zero-tolerance policy on conduct that is incompatible with the aims and objectives of the United Nations and FAO, including sexual exploitation and abuse, sexual harassment, abuse of authority, and discrimination
  • All selected candidates, therefore, will undergo rigorous reference and background checks
  • All applications will be treated with the strictest confidentiality
  • The incumbent may be re-assigned to different activities and/or duty stations depending on the evolving needs of the Organization

Organizational Setting

The Office of Chief Statistician (OCS) is mandated to strengthen the coordination of FAO statistical activities and to oversee the implementation of the organization’s responsibilities in global SDG reporting. Furthermore, OCS sets statistical standards for all data collection and dissemination activities of the organization

During 2019, OCS launched the Food and Agricultural Microdata (FAM) Catalogue aiming to create a one-stop-shop for finding
microdata on agriculture. FAM serves as the corporate solution for disseminating microdata collected directly or supported by FAO,
as well as, disseminates micro datasets relevant to FAO’s mandate which are already disseminated on national platforms. The set-up and maintenance costs of FAM during 2019-2021 are supported by United States Agency for International Development (USAID) and Bill & Melinda Gates Foundation (BMGF) through the Agricultural and Rural Integrated Survey (AGRISurvey) program.A new project proposal has been developed to continue the FAM activities for the next three years and the resource mobilization is underway.

Reporting Lines

Consultants and PSA subscribers in OCS will work under the immediate supervision of the Chief Statistician. They are required to work in close collaboration with the other staff in OCS and with the relevant teams in ESS.

Technical Focus

Technical units and data providers submit microdata and accompanying documentation to OCS for dissemination through the FAM
catalogue. For quality assurance purposes, OCS performs various data quality checks and applies Statistical Disclosure Control (SDC) techniques to ensure that the data subjects’ identities are protected. All of the quality checks, and application of SDC methods are implemented in R markdown to ensure that the process is properly documented.

In this regard, a consultant will undertake the quality checks, and anonymization of the microdata. In addition, the consultant will support the computation of some selected SDG indicators using national level data obtained from countriesThe consultant must have experience applying statistical methods to household survey and/or farm survey data and be proficient with R. He/she must have knowledge, experience, or the capacity to apply SDC methods.

Tasks and responsibilities

• Support OCS in Identifying relevant datasets in external catalogues, harvest data, and draft DDI compliant metadata
• Collect datasets, anonymize and organize microdata files, develop DDI-compliant metadata, and publish in ACS the following datasets:
o Food Insecurity Experience Scale (FIES) datasets
o Datasets received from external provider
o Datasets received from various internal technical departments
• Update the Shiny application to perform all of the required data quality control checks
• Develop codes in R or in STATA or in CSpro for computing selected SDG indicators using national level data
• Update all SDG data visualizations in the SDG portal using Tableau
• Upload the harmonized SDG data export files in Artifactory
• Generate a bulk download file containing all SDG indicator data


Minimum Requirements

• University degree (advanced degree preferred) in Statistics, Economics, Public Policy, or related field / University degree (only for PSA) in Statistics, Economics, Public Policy, or related field.
• Minimum 1 year of relevant experience in applying statistical methods to household or farm survey datasets
• Working knowledge of English, and limited knowledge of French, Spanish, Chinese, or Russian for COF.REG. Working knowledge of English for PSA.SBS.

FAO Core Competencies

• Results Focus
• Teamwork
• Communication
• Building Effective Relationships
• Knowledge Sharing and Continuous Improvement

Technical/Functional Skills

• Experience cleaning, and analysing household and/or farm survey datasets
• Knowledge of statistical disclosure control methods and tools
• Prior experience working on microdata dissemination
• Knowledge of or direct experience working with national statistical systems would be an advantage
• Good knowledge on one or more of the statistical software like R, STATA, CSPro, SPSS

Please note that all candidates should adhere to FAO Values of Commitment to FAO, Respect for All and Integrity and Transparency

We do our best to provide you the most accurate info, but closing dates may be wrong on our site. Please check on the recruiting organization's page for the exact info. Candidates are responsible for complying with deadlines and are encouraged to submit applications well ahead.
Before applying, please make sure that you have read the requirements for the position and that you qualify.
Applications from non-qualifying applicants will most likely be discarded by the recruiting manager.

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