The United Nations World Food Programme (WFP) is the world's largest humanitarian organization, working to save lives and combat hunger globally. In Yemen, one of the world's most severe humanitarian crises continues to drive widespread food insecurity and vulnerability. According to the 2026 Humanitarian Needs and Response Plan (HNRP), an estimated 22.3 million people require humanitarian assistance, including 18.3 million people in need of food security and livelihood support. WFP's response focuses on saving lives, protecting livelihoods, and improving food consumption among the most vulnerable populations through life-saving food assistance and nutrition interventions. To support evidence-based programming and strategic decision-making, WFP Yemen's Vulnerability Analysis and Mapping (VAM) unit leads food security monitoring, assessments, and analysis across the country. The unit conducts large-scale food security and livelihood assessments, market monitoring, beneficiary monitoring, and other analytical activities that generate critical information on food security conditions, market trends, household vulnerabilities, and humanitarian needs. These efforts provide the evidence base for Programme design, targeting, operational planning, donor engagement, resource mobilization, and advocacy. The VAM unit manages and analyzes a wide range of datasets and produces regular analytical products, including monthly food security updates, quarterly food security and market monitoring and market functionality assessments. Through rigorous data collection, analysis, and reporting, the unit plays a central role in informing WFP's response and supporting humanitarian decision-making across Yemen.

The VAM Officer (Statistician) will support the design, implementation, and analysis of food security assessments and surveys by applying sound statistical methodologies and ensuring the quality, accuracy, and reliability of data collected by WFP Yemen. The position is responsible for conducting statistical analyses and modeling, developing sampling methodologies, managing survey datasets, and producing evidence-based findings to inform food security monitoring, Programme implementation, and humanitarian response. The incumbent will contribute to questionnaire design, sample selection, data cleaning, validation, weighting, and quantitative/qualitative analysis of food security, market, and beneficiary datasets. The role will support the preparation of analytical reports, statistical tables, dashboards, and other information products while ensuring adherence to WFP standards and best practices in survey design, data quality assurance, and statistical reporting. The position will also support the application of innovative statistical techniques including Artificial Intelligence and Machine Learning approaches and strengthen the quality and credibility of evidence generated by the VAM unit.

• Support the design and implementation of food security, market prices and market functionality, beneficiary targeting, and ad hoc assessments by applying appropriate statistical methods and ensuring methodological rigor throughout the assessment cycle.
• Develop sampling methodologies, sample frames, and sample size calculations for household surveys, market assessments, monitoring activities, and other evidence-generation exercises conducted by WFP Yemen.
• Lead data processing activities, including data cleaning, validation, weighting, imputation, and preparation of analysis-ready datasets, ensuring accuracy, consistency, and adherence to established quality standards.
• Conduct statistical analyses of food security, livelihoods, market, beneficiary, and vulnerability datasets using WFP corporate techniques of quantitative and qualitative data analysis.
• Support the development, calculation, and validation of key food security, market, targeting, and outcome indicators used in WFP monitoring and assessment systems.
• Ensure quality assurance of data collection processes through development of validation rules, consistency checks, field monitoring tools, and data quality assessment procedures.
• Contribute to the design, testing, and refinement of questionnaires, survey instruments, and digital data collection tools to improve data quality and operational efficiency.
• Develop and maintain statistical code, automated scripts, and reproducible analytical workflows using relevant statistical software and programming languages to improve efficiency and standardization of analyses.
• Support advanced quantitative analyses, including trend analysis, predictive modelling, small-area estimation, targeting analysis, and other analytical techniques required for food security monitoring and humanitarian response.
• Prepare statistical tables, analytical datasets, metadata, technical documentation, and methodological notes to support reporting and ensure transparency and reproducibility of analytical outputs.
• Support the production of periodic analytical products by providing robust statistical evidence, indicator calculations, and quantitative findings for reports, dashboards, briefs, and other information products.
• Contributes to the integration and harmonization of diverse datasets, including household, market, targeting, operational, geographic, and secondary data sources, to strengthen analytical capacity within the VAM unit.
• Provide technical guidance and training to VAM staff, field teams, cooperating partners, and government counterparts on survey implementation, sampling methodologies, data quality management, and statistical analysis techniques.
• Support emergency assessments and rapid response analytical efforts by conducting timely statistical analysis and ensuring the availability of reliable evidence during crises and sudden-onset emergencies.
• Maintain statistical standards, documentation, and archiving systems to ensure compliance with WFP policies, best practices, and data protection requirements.
• Provide GIS and geospatial data-analysis and management support, including geocoding, spatial joins, administrative boundaries, vulnerability layers, operational locations and map production, where applicable.
• Develop and maintain dashboards and automated reporting products for food security, market prices, assessment results, rM&E/mVAM and other priority VAM indicators.

Desired Candidate Profile

University degree in Statistics, Applied Statistics, Mathematics, Econometrics, Data Science, or a related quantitative discipline, with strong training in survey methodology, sampling, statistical modelling, and quantitative analysis.

Total relevant 5 years of experience including 1 year of Professional experience in statistics, quantitative/qualitative analysis, survey methodology, data management, monitoring and evaluation, food security analysis, economics, or a related field.

Experience in survey design, sampling methodologies, statistical analysis, data quality assurance, and management of large datasets is highly desirable.

Experience working with humanitarian, development, or socio-economic data and proficiency in statistical software packages like R, STATA, SPSS, Python would be necessary.