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International Consutant: Trade Data Processing
Job in
Genf, Geneva, Switzerland
Listed on 2026-07-18
Listing for:
United Nations
Full Time
position Listed on 2026-07-18
Job specializations:
-
IT/Tech
Data Engineering, Data Entry
Job Description & How to Apply Below
Job Opening
Job Opening : 281173
Job Family: Programme Management
Category and Level: Affiliate Personnel – Consultants/Individual Contractors, CON
Recruitment Type: Consultant
Duty Station: GENEVA
Department/Office: International Trade Centre
Date Posted: Jul 15, 2026
Responsibilities
- Deliverable 1 – September 2026:
By 30 September 2026, collect, validate, format and integrate into the Trade Map production database the available trade in goods and trade in services datasets for assigned countries, ensuring that all scheduled updates are completed within agreed timelines. Submit a brief monthly processing summary highlighting datasets processed, quality issues identified and corrective actions taken. - Deliverable 2 – October 2026:
By 31 October 2026, process and integrate the monthly and newly released trade statistics for assigned countries, applying all required quality assurance checks and documenting any anomalies, methodological deviations or data corrections. Maintain and update the associated processing scripts and technical documentation as required. - Deliverable 3 – November 2026:
By 30 November 2026, complete the processing and integration of all assigned trade in goods and services datasets scheduled during the contract period, ensuring that data quality controls have been successfully completed and documented. Submit a final processing report summarizing outputs delivered, improvements introduced and recommendations for subsequent processing cycles. - Expected Results:
Ensure that trade statistics for at least 25 reporting countries have been collected, validated, formatted and integrated into the Trade Map database in accordance with established procedures. Maintain and update trade in services data processing procedures to ensure timely publication. Apply data quality assurance checks consistently. Update processing scripts, technical documentation and workflow records to support operational reliability.
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