Senior Survey Methodology Expert

About the role

NTU International is seeking a Senior Survey Methodology Expert to lead the design and implementation of agricultural survey systems for an EU‑funded project supporting Uzbekistan’s Agri‑Food Development Strategy. The role will ensure high‑quality data collection and statistical standards to inform policy and monitoring.

Key responsibilities

• Develop and implement agricultural survey methodologies and statistical data collection systems.
• Provide technical assistance on survey design, sampling, questionnaire development and statistical quality assurance.
• Design methodologies for farm surveys, household surveys, agricultural censuses and sector monitoring.
• Advise public institutions on survey planning, data validation, statistical standards and digital data collection tools.
• Integrate innovative techniques, GIS tools and digital monitoring into agricultural statistics frameworks.
• Analyse survey reliability, statistical consistency and data quality management.
• Prepare methodological guidelines, technical manuals, analytical reports and statistical procedures.
• Coordinate with ministries, national statistical offices, research institutions and development partners.
• Deliver workshops, training and capacity‑building activities on survey methodologies.
• Support monitoring, reporting and evaluation of agricultural data collection and statistical reform initiatives.

Required profile

• Master’s degree in statistics, econometrics, mathematics, economics, agricultural economics or a related field.
• Minimum 10 years of professional experience in survey methodologies, statistical systems or quantitative analysis, preferably in agricultural or public‑sector reform projects.
• At least 7 years of hands‑on experience in survey design, sampling, agricultural censuses or household surveys.
• Experience working on international development cooperation and donor‑funded programmes.

Required skills

• Survey design
• Sampling methodologies
• Questionnaire development
• Statistical quality assurance
• GIS tools
• Digital data collection
• Data validation
• Statistical standards