Statistics Specialist

Organizational Setting

The Regional Office for Near East and North Africa (RNE) is responsible for leading FAO's response to regional priorities for food security, agriculture and rural development through the identification, planning and implementation of FAO's priority activities in the region. It ensures a multidisciplinary approach to programmes, identifies priority areas of action for the Organization in the region and, in collaboration with Offices, Centres and Divisions at headquarters, develops, promotes and oversees FAO's strategic response to regional priorities. RNE also advises on the incorporation of regional priorities into the Organization's Programme of Work and Budget and implements approved programmes and projects in the region, monitors the level of programme implementation and draws attention to problems and deficiencies. RNE develops and maintains relations with region-wide institutions including the Regional Economic Integration Organizations (REIOs).

In collaboration with the Statistics Division, and other statistical units at FAO headquarters, and in close consultation with the Chief Statistician, it supports countries in the production and dissemination of high-quality statistics in the areas of food security and nutrition, agriculture, rural development and sustainable management of natural resources. It also facilitates the implementation of a number of large scale global statistical programmes (World Census of Agriculture Programme 2030, 50x2030 Initiative, Global Strategy for improving Agricultural and Rural Statistics-GSARS, Food Insecurity Experience Scale-FIES) aimed at improving statistical methodologies in the countries and establishing best practices for the collection, collation, processing, dissemination and use of data relevant to food security and nutrition, agriculture and rural development

Reporting Lines

Consultants and PSA subscribers will work under the immediate technical supervision of the Statistician of FAO Regional Office for Near East and North Africa and the general oversight of the FAO Representatives of countries they will be supporting. They may be called upon to collaborate with other FAO divisions, units and teams. 

Technical Focus 

Consultants and PSA subscribers will work on the preparation and implementation of statistical operations of different domains described above through the development and/or review of methodology and technical documents, supporting data collection, data processing, data analysis and dissemination. They will also provide capacity development to various countries on compilation, analysis and quality assurance of statistical processes and products in different areas of agricultural statistics FAO staff, government counterparts and implementing partners to address gender equality and women empowerment in their respective areas of work.

Tasks and responsibilities

Consultants and PSA subscribers will contribute to and/or take responsibility for one or more of the following tasks: 

•    Develop methodology and technical documents for agricultural censuses and surveys (Questionnaires, sample design, instruction and training manuals, tabulation and analysis plans); 
•    Develop methodologies (for data processing, imputation of missing data, validation, and quality control); 
•    Collect, process, analyse and validate data; write reports and disseminate data at national and sub-national level; 
•    Compile food balance sheets and supply utilization accounts to generate nutrient statistics; 
•    Demonstrate proficiency in using widely adopted statistical software tools that are commonly employed in data analysis and research across various fields;
•    Use technologies for data collection (CAPI, CSPro, Survey Solutions, Remote Sensing, Crowdsourcing, Web scraping, etc.);
•    Analyse agricultural censuses and surveys data, including indicators computation;
•    Design, prepare and manage statistical projects; 
•    Perform statistical capacity development, including needs assessments, design and implementation of statistical training and technical assistance activities; 
•    Perform statistical policy advocacy, communication and implementation; 
•    Conduct strategic planning in agricultural and rural statistics; 
•    Use administrative data in agricultural and rural statistics; 
•    Archive communication and disseminates statistical products; 
•    Perform any other related duties, as required.

CANDIDATES WILL BE ASSESSED AGAINST THE FOLLOWING

Minimum Requirements

•    University degree in statistics, data science, mathematics, economics, agricultural sciences, or a related and relevant fields. 
•    At least 3 years of relevant experience in any of the above-mentioned statistical areas of work and / or fields of application.
•    Full proficiency/Working knowledge of English (level C).  

FAO Core Competencies

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

Technical/Functional Skills 

•    Extent and length of knowledge and experience in performing the above-mentioned tasks and responsibilities in relevant statistical fields; 
•    Ability to draft quickly, clearly and concisely and to communicate effectively in English; 
•    Ability to use Survey Solutions, CSPro, Kobo Toolbox or equivalent software, and data processing and analysis software such as R, Stata, SPSS, or analogous ones;
•    Ability to work independently, with minimum supervision; 
•    Previous working experience with FAO or its partners (including countries) in the above-mentioned statistical domains and tasks; 
•    Strong command of statistical methods including: data presentation, data validation, imputation of missing values, analysis and descriptive statistics; main continuous and discrete random variables (binomial, normal, standard normal, log-normal) and their properties; probability distributions; conditional probability, probabilities of intersections of events, Bayes' theorem; correlation and rank correlation; sampling and sample size: simple, stratified, and multistage random sampling; Inference, confidence intervals, hypothesis testing and significance; linear regression (single and multiple) comparison of population means and variances, ANOVA; Chi-square and goodness of fit tests; nonlinear models: maximum likelihood estimation; elements of agricultural censuses/surveys and questionnaires design; data processing workflow and principles; agricultural census/survey planning;

Selection Criteria

•    Knowledge of Arabic and limited knowledge of French is considered an asset