FAO Technical Specialist in Advanced Methods for Economic Modelling
Food and Agriculture Organization of the United Nations (FAO)
Job Description
Job Posting Organization:
The Agrifood Economics and Policy Division (ESA) of the FAO is dedicated to conducting economic research and policy analysis aimed at transforming agrifood systems to be more efficient, inclusive, resilient, and sustainable. The organization focuses on better production, nutrition, environment, and overall quality of life, ensuring that no one is left behind. ESA provides evidence-based support to various policy processes and initiatives at national, regional, and global levels, addressing issues such as security" style="border-bottom: 1px dotted #007bff !important;">security" style="border-bottom: 1px dotted #007bff !important;">food security, agricultural policies, and rural transformation. The division is responsible for producing key publications like The State of Food and Agriculture (SOFA) and The State of Food Security and Nutrition in the World (SOFI), and it plays a crucial role in the FAO Global Roadmap.
Job Overview:
The Technical Specialist position is centered around advanced data analysis, particularly utilizing mathematical and machine learning methods to enhance the understanding of agrifood systems. The role involves dimensional reduction of complex agrifood indicators to create lower-dimensional representations, which are essential for tracking national progress towards sustainable agrifood systems. The incumbent will contribute to significant reports and platforms that monitor food insecurity and assess future scenarios related to undernourishment and poverty. This position requires innovative thinking and the ability to analyze and model complex data, ultimately supporting flagship FAO initiatives and improving the assessment and forecasting of food security outcomes.
Duties and Responsibilities:
The Technical Specialist will undertake a variety of tasks, including: developing and applying machine learning models for prediction and classification; contributing to food insecurity forecasting and risk monitoring; enhancing data processing and model performance; supporting the acquisition and quality assurance of large datasets; utilizing programming languages for advanced data analysis; contributing to global macroeconomic simulation models; analyzing uncertainty and model sensitivities; applying advanced analytical methods to assess risks affecting agrifood systems; communicating complex concepts to diverse audiences; engaging with stakeholders; preparing technical documentation; and representing the team in meetings and conferences.
Required Qualifications:
Candidates must possess an advanced university degree in economics, mathematics, physics, computer sciences, or statistics from a recognized institution. Those with a bachelor's degree must have two additional years of relevant professional experience. A minimum of 5 years of relevant experience in quantitative analysis of agrifood systems is required, particularly in applying advanced models to sustainable agrifood systems or food insecurity. A working knowledge of English at level C is mandatory.
Educational Background:
The educational background required for this position includes an advanced university degree from an institution recognized by the International Association of Universities (IAU)/UNESCO in relevant fields such as economics, mathematics, physics, computer sciences, or statistics. For those with a bachelor's degree, additional professional experience is necessary to meet the qualifications.
Experience:
The position requires at least 5 years of relevant experience in quantitative analysis, specifically related to agrifood systems. This includes applying advanced models to address issues of sustainability and food insecurity. Candidates should have a strong background in data analysis and modeling within the context of agrifood systems.
Languages:
A working knowledge of English (level C) is mandatory for this position. Proficiency in additional languages may be beneficial but is not specified as a requirement.
Additional Notes:
The job posting does not specify a deadline for applications. The position is remote, allowing for flexibility in work location. Candidates will be assessed based on their qualifications, experience, and competencies related to the role. The FAO emphasizes core competencies such as results focus, teamwork, communication, and building effective relationships, alongside technical skills in mathematical methods and data analysis.
The Agrifood Economics and Policy Division (ESA) of the FAO is dedicated to conducting economic research and policy analysis aimed at transforming agrifood systems to be more efficient, inclusive, resilient, and sustainable. The organization focuses on better production, nutrition, environment, and overall quality of life, ensuring that no one is left behind. ESA provides evidence-based support to various policy processes and initiatives at national, regional, and global levels, addressing issues such as security" style="border-bottom: 1px dotted #007bff !important;">security" style="border-bottom: 1px dotted #007bff !important;">food security, agricultural policies, and rural transformation. The division is responsible for producing key publications like The State of Food and Agriculture (SOFA) and The State of Food Security and Nutrition in the World (SOFI), and it plays a crucial role in the FAO Global Roadmap.
Job Overview:
The Technical Specialist position is centered around advanced data analysis, particularly utilizing mathematical and machine learning methods to enhance the understanding of agrifood systems. The role involves dimensional reduction of complex agrifood indicators to create lower-dimensional representations, which are essential for tracking national progress towards sustainable agrifood systems. The incumbent will contribute to significant reports and platforms that monitor food insecurity and assess future scenarios related to undernourishment and poverty. This position requires innovative thinking and the ability to analyze and model complex data, ultimately supporting flagship FAO initiatives and improving the assessment and forecasting of food security outcomes.
Duties and Responsibilities:
The Technical Specialist will undertake a variety of tasks, including: developing and applying machine learning models for prediction and classification; contributing to food insecurity forecasting and risk monitoring; enhancing data processing and model performance; supporting the acquisition and quality assurance of large datasets; utilizing programming languages for advanced data analysis; contributing to global macroeconomic simulation models; analyzing uncertainty and model sensitivities; applying advanced analytical methods to assess risks affecting agrifood systems; communicating complex concepts to diverse audiences; engaging with stakeholders; preparing technical documentation; and representing the team in meetings and conferences.
Required Qualifications:
Candidates must possess an advanced university degree in economics, mathematics, physics, computer sciences, or statistics from a recognized institution. Those with a bachelor's degree must have two additional years of relevant professional experience. A minimum of 5 years of relevant experience in quantitative analysis of agrifood systems is required, particularly in applying advanced models to sustainable agrifood systems or food insecurity. A working knowledge of English at level C is mandatory.
Educational Background:
The educational background required for this position includes an advanced university degree from an institution recognized by the International Association of Universities (IAU)/UNESCO in relevant fields such as economics, mathematics, physics, computer sciences, or statistics. For those with a bachelor's degree, additional professional experience is necessary to meet the qualifications.
Experience:
The position requires at least 5 years of relevant experience in quantitative analysis, specifically related to agrifood systems. This includes applying advanced models to address issues of sustainability and food insecurity. Candidates should have a strong background in data analysis and modeling within the context of agrifood systems.
Languages:
A working knowledge of English (level C) is mandatory for this position. Proficiency in additional languages may be beneficial but is not specified as a requirement.
Additional Notes:
The job posting does not specify a deadline for applications. The position is remote, allowing for flexibility in work location. Candidates will be assessed based on their qualifications, experience, and competencies related to the role. The FAO emphasizes core competencies such as results focus, teamwork, communication, and building effective relationships, alongside technical skills in mathematical methods and data analysis.
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We are not liable for any decisions or actions taken by applicants in response to this job listing. By applying, you agree that all application processes, interviews, and potential job offers are managed exclusively by the listed employer or organization.
Beware of fraudulent job offers. Do not provide sensitive personal information or make any payments to secure a job.