Data Analysis Specialist

Overview

Support effective programme operations and data management.

You have:

• Advanced university degree from an institution recognized by IAU/UNESCO with specialization in international development, natural resource management, or related fields. Alternatively, a first-level degree and two additional years of relevant experience may be considered.
• University degree (or technical degree/certificate) from an institution recognized by IAU/UNESCO with specialization in international development, natural resource management, or related fields.
• Minimum of 1 year of relevant working experience in programme or project support, preferably within FAO or U.N. Agencies/organizations.
• Working knowledge (level C) of English.
• Limited knowledge (intermediate - level B) of another official FAO language (Arabic, Chinese, French, Russian or Spanish) is an asset.

Organizational Setting

The Forestry Division (NFO) leads FAO's work in promoting sustainable forest management and providing leadership on the environmental, social and economic dimensions of forestry, including its contributions to poverty reduction and food security and nutrition. It liaises with Members, civil society and the private sector in aspects ranging from development of effective forest policies to forest conservation and management issues and strengthens the role of forests in climate change mitigation and adaptation. The Division also collects, analyses and disseminates information on the world's forest resources and on the production, trade and consumption of wood and non-wood forest products. The Forest and Farm Facility (FFF) Team is a partnership between FAO, the International Union for Conservation of Nature (IUCN), the International Institute for Environment and Development (IIED) and AgriCord, housed in the NFO and supported under an umbrella programme and a multi-donor Trust Fund, focusing on climate-resilient landscapes and improved livelihoods. FFF sees the Forest and Farm Producer Organizations (FFPOs) which represent smallholders, rural women's groups, local communities and indigenous peoples' institutions as the key agents of change in rural landscapes. The position is located in the Forest and Farm Facility (FFF) Team of the Forestry Division (NFO) at FAO headquarters in Rome, Italy.

Reporting Lines

The Specialist will work under the overall supervision of the Manager/OiC of the Forest and Farm Facility (FFF) and the direct supervision of the Lead FFF Forestry Officer and Monitoring- Reporting Specialist. They may be called upon to collaborate with other FAO Divisions and teams.

Technical Focus

The incumbent will support effective programme operations, coordination, and delivery. The Data Analyst will provide specialized technical expertise in the design, development, maintenance, and continuous improvement of consolidated databases and digital platforms contributing to strengthen programme monitoring, reporting, and evaluation and learning (MEL) systems as well as knowledge management by integrating, analysing, and visualizing programme data to generate actionable insights for programme management, reporting, and strategic decision-making. In addition, the position provides operational support in the preparation of analytical outputs, dashboards, presentations, and communication materials for internal and external audiences.

Tasks and responsibilities

The incumbent will contribute to and/or take responsibility for one or more of the following tasks:

Data Analysis Specialist

• Provide technical expertise in the implementation of innovative data management and systems development to strengthen monitoring, evaluation, and learning (MEL) systems, with a focus on data integration, analytics and data visualization. • Conduct exploratory data analysis and analytical assessments to identify patterns and trends in forestry-related livelihood activities and their impact on programme outcomes, including data insights, financial dashboards. • Develop, maintain and optimize integrated databases and data management platforms ensuring the integration, quality, consistency, and accessibility of programme data across multiple sources and systems. • Review and enhance qualitative and quantitative technical documentation to improve data quality, consistency, analytical value and reporting standards. • Develop data visualizations, analytical dashboards and communication materials, using Power BI, Excel, Tableau to support the effective dissemination of programme results and evidence-based decision-making.

CANDIDATES WILL BE ASSESSED AGAINST THE FOLLOWING

Minimum Requirements

• For Consultants: Advanced university degree from an institution recognized by the International Association of Universities (IAU)/UNESCO with specialization in international development, natural resource management, business administration, economics, social sciences, environmental science, economics. In alternative, a first-level degree and two additional year of relevant experience may be considered. • For PSA.SBS: University degree (or technical degree/certificate) from an institution recognized by the International Association of Universities (IAU)/UNESCO with specialization in international development, natural resource management, business administration, economics, social sciences, environmental science, economics • Minimum of 1 year of relevant working experience in programme or project support, preferably within FAO or U.N. Agencies/organizations. • Working knowledge (level C) of English.

FAO Core Competencies

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

Technical/Functional Skills

• Strong organizational, analytical, and writing skills. • Familiarity with FAO’s contractual modalities and operational procedures is an asset.

Selection criteria:

• Limited knowledge (intermediate - level B) of another official FAO language (Arabic, Chinese, French, Russian or Spanish) is an asset

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Potential interview questions

Added 18 days ago - Updated 4 days ago - Source: fao.org