International Consultant-Technical Support,Hanoi,Vietnam,Remotely,6 Months (Open For International Candidates) Req#595841

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Contract type: Consultant
Duty Station: Hanoi
Level: Consultancy
Location: Viet Nam
Categories: Research, Planning, Monitoring and Evaluation
Contract Duration: 6 Months
Working arrangement: Home Based
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The Multiple Indicator Cluster Surveys (MICS) programme is UNICEF's international household survey programme run together with national statistics offices designed to collect high-quality data on the situation of children, women, and households.
In preparation for the next MICS in Viet Nam, the National Statistics Office (NSO) of Viet Nam expressed interest in transitioning from a paper-based management of enumeration areas (EAs) to a digital geospatial framework to support MICS and other future household surveys.
Viet Nam conducted its most recent Population and Housing Census in 2019. The Census cartography - which was primarily paper based - serves as the master sample frame for other national population-based surveys.
After the recent administrative reform in July 2025, 63 provinces have been merged into 34 and 10,035 communes have been merged into 3321 with new commune boundaries.
In this context, the NSO is required to update the master sample frame using new provincial and commune boundaries. At the same time, in line with digital transformation policy, NSO is interested in developing a national digital geospatial database of EAs that can serve as a permanent geographic reference framework for survey and census operations.
Such a framework would support sample design, sample selection, household listing, fieldwork management, weighting, dissemination, and future statistical activities.
The development of a digital master sample EA framework requires the assessment, preparation, and integration of multiple geospatial datasets, including administrative boundaries, structure coordinates, population estimates, building footprints, roads, waterways, and other geographic features.
In addition, the resulting framework should provide standardised metadata for each EA, including population estimates, household counts, administrative identifiers, and urbanisation classifications
The purpose of this assignment is to support the NSO of Viet Nam in developing a national digital geospatial EA framework for MICS and other household surveys, while strengthening national capacity for its maintenance, updating and future use.
UNICEF, in collaboration with the NSO, will recruit a team of an international consultant and a national consultant to undertake this assignment. This ToR is for recruiting an international consultant, but the context and expected team work are presented for candidates to understand the situation and the national resources he/she will have.
The two consultants will operate as an integrated technical team.
The international consultant will lead methodological design, comparative analysis, technical specifications, quality standards, advanced programming, documentation and training design.
The national consultant will lead or support national data access, contextual interpretation, data preparation, local testing, production processing, liaison with NSO units, validation, documentation and hands-on knowledge transfer.
The work of both consultants needs to be closely coordinated to avoid duplication and to ensure that technical knowledge, source code and operational ownership are transferred to the NSO.
Scope Of Work
Under the supervision of UNICEF and in close collaboration with the NSO of Viet Nam, the international consultant will undertake the following activities:
Methodology development of the digital EA framework
Develop and document a methodology for digital EA delineation based on publicly available data sources.
Define operational criteria for EA creation, including household thresholds, geographic constraints, and administrative requirements.
Define and document the authoritative coordinate reference system and transformation workflow. Project outputs shall support VN-2000 using the officially applicable parameters and central meridians and, where required for interoperability, WGS84. The consultant shall document all source coordinate systems, transformations, precision implications and quality checks, and shall not apply unverified transformation parameters.
Using publicly available data sources, design a pilot of delineation of NSO’s selected EAs for manual review and validation by the national consultant and NSO.
Ensure consistency with the best international practices for survey sampling frames.
Assessment and preparation of geospatial data
Review actual census cartographic materials, sampling frame documentation, and existing geospatial datasets provided by NSO.
Assess the spatial and attribute alignment between the 2019 EA framework and the latest officially approved administrative boundaries at all relevant levels. Identify splits, mergers, code changes, boundary mismatches, gaps, overlaps and lineage issues, and develop a documented crosswalk and synchronisation approach that preserves traceability between the 2019 census geography and the current administrative structure.
Review and, where necessary, clean, harmonise, and prepare datasets required for EA delineation.
Review transportation networks, waterways, and other geographic features that may support EA delineation, and identify opportunities for improvement.
Assess requirements for updating population estimates and generating supporting population surfaces where required.
Identify data gaps and recommend solutions where necessary.
Agree with the NSO and the national consultant on the master sample areas covering dense urban, peri-urban, rural, remote, mountainous, coastal or riverine, and other operationally relevant contexts, as permitted by available data.
Define a documented data-readiness assessment, including minimum data requirements, expected limitations, treatment of missing or conflicting data, and implications for national scalability.
Ensure that data preparation and analytical workflows can be reproduced using R and/or Python scripts.
Validation and enhancement
Develop measurable quality assurance and acceptance criteria covering invalid geometry, gaps, overlaps, slivers, multipart geometries, non-contiguous EAs, administrative-boundary violations, duplicate or missing identifiers, missing metadata, implausible values and deviations from agreed thresholds.
Specify mandatory validation technical and operational validation with the national consultant and NSO staff across representative urban, rural and geographically complex areas.
Maintain a validation and decision log, refine the selected or hybrid workflow based on feedback, and prepare final geospatial datasets, metadata, code, configuration files and QA outputs.
Capacity building and knowledge transfer
Design and deliver a comprehensive five-day, in-person, hands-on training programme for NSO staff, jointly supported by the national consultant.
Prepare a competency-based package enabling participants to understand, execute, compare, validate, modify and maintain the EA workflows rather than only observe demonstrations.
Structure the workshop broadly as follows:
Day 1 - data architecture, readiness and preparation
Day 2 - concepts and demonstrations approaches
Day 3 - supervised implementation and comparison
Day 4 - QA, validation, metadata, classifications and refinement
Day 5 - production workflow, maintenance, code adaptation, governance, participant assessment and handover planning.
Provide presentations, instructor and participant guides, step-by-step exercises, training datasets, expected outputs, troubleshooting notes, glossary, fully commented scripts or notebooks, and pre- and post-training competency assessments.
Ensure participants have sufficient hands-on time to run, inspect, modify and troubleshoot the code with support from both consultants, and transfer all editable source materials for internal reuse.
Documentation and recommendation
Document all datasets, assumptions, methods, algorithms, parameters, decisions, workflows, exceptions, outputs and limitations.
Deliver a structured reproducible source-code repository containing fully commented R and/or Python scripts or notebooks, configuration files, sample commands, package and environment specifications, data dictionaries, README files, folder structures, processing logs and troubleshooting guidance.
Ensure that no essential step is a

Work arrangement
Yes