Statistics is a core function of FAO and represents a highly visible area of the Organization’s work. FAO is recognized as having a fundamental global role in developing methods and standards for food and agriculture statistics and as hosting the world’s largest statistical database for food and agriculture statistics, FAOSTAT. In addition to maintaining the collection, processing and dissemination of existing data series, there are increasing demands for new statistics.
The Methodological innovation team is responsible for the development of methods, standards, tools, norms and classifications used mainly within the organization with the objective to improve the efficiency of FAO’s statistical system and the quality of its output.
Ongoing activities relate to the review of the approach and methods towards the preparation of Food Balance Sheets, a flagship statistical product, with particular emphasis on a rules-based framework for production imputation (using an ensemble approach), trade balancing, allocation of domestic supplies to domestic utilization as well as estimating elements of expected utilization, e.g. food, animal feed, seed, losses (using linear and non-linear parametric models).
Future activities will cover other statistical domains (agricultural prices, agro-environmental indicators, fisheries and forestry statistics). The consultant will contribute to the development of improved methods and processes with a focus on imputation methods for missing data, compilation of regional and world aggregates, data analysis and validation methods.
By way of example, with respect to methodological and technical work on Food Balance Sheet (FBS), the consultant would undertake the following duties:
– Develop optimum imputation, analysis and/or validation methods for improved Supply Utilization Accounts (SUA’s) and FBS;
– Test and implement optimum statistical methods;
– Provide high-level recommendations on ways to implement the estimation and calculation of SUA elements (stocks, feed, seed, post-harvest losses and waste, and food consumption) in R and on the module architecture, and deliver script in accordance.
– Oversee the development of computational plug-ins in R script to be used in the new statistical working system.
– Document the statistical methods and corresponding R scripts.
– Develop validation routines .
– Analyse pilot results and validate data.
Core skills:
- Dynamic statistician equipped with both highly advanced statistical skills and R-programming skills and as well as with the ability to quickly master and apply new methods.
- Ability to make recommendations and advise decision-makers on highly technical issues.
- General understanding of databases and complex technological systems.
- Ability to understand statistical user requirements
- Ability to design a module architecture
- Proven ability to self-start, progress quickly up a steep learning curve, assume initiative and to multi-task.
- Focus on delivery and on meeting tight deadlines.
- Knowledge of agricultural statistics and/or food commodities would be an advantage.
- Effective collaborator, in particular familiar with Github.
- Postgraduate in statistics or other relevant quantitative field.