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Tender description :
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Tender Are Invited For TECHNICAL EXPERT ON CENSUS DATA PROCESSING FOR THE 2026 AGRICULTURE AND FISHERIES CENSUS
The OECS Data for Decision Making (DDM) Project (the Project) is a regional project that seeks
to strengthen the capacity of participating Eastern Caribbean countries to produce and publicly
disseminate statistical data for country- and regional-level analysis. It will be implemented by
Grenada, Saint Lucia, Saint Vincent and the Grenadines, and the OECS Commission. The Project
seeks to achieve its objective by strengthening national- and regional-level capacities and fostering
regional coordination.
The Statistical Office, a unit within the Economic Planning Division of the Ministry of Finance
and Economic Planning, is the principal producer of official statistics in Saint Vincent and the
Grenadines. While the Statistical Office is responsible by law for conducting censuses and surveys,
it has delegated this authority to the Ministry of Agriculture, Forestry and Rural Transformation
(MAFRT) for the Census of Agriculture and Fisheries (CAF). Data collection for the CAF
commenced on March 9, 2026, using the Survey Solutions platform, and is expected to be
completed by October 30, 2026.
A Technical Expert on Census Data Processing assesses the quality of collected census data and
designs and applies the methodology needed to transform it into a reliable final database. This
includes developing data cleaning, coding, imputation and validation procedures, producing
statistical tables and metadata, training national staff, and ensuring that census data is handled
securely and in accordance with statistical confidentiality standards.
The Project is seeking to engage an experienced Individual Consultant to develop a data
processing methodology for the CAF database based on international best practices, and to apply
that methodology in collaboration with MAFRT staff to produce a high-quality, fully validated,
anonymized and analysis-ready CAF 2026 database and statistical tables, consistent with national,
regional and international statistical standards.
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