About UNICEF

If you are a committed, creative professional and are passionate about making a lasting difference for children, the world's leading children's rights organization would like to hear from you. For 70 years, UNICEF has been working on the ground in 190 countries and territories to promote children's survival, protection and development. The world's largest provider of vaccines fordeveloping countries, UNICEF supports child health and nutrition, good water and sanitation, quality basic education for all boys and girls, and the protection of children from violence, exploitation, and AIDS. UNICEF is funded entirely by the voluntary contributions of individuals, businesses, foundations and governments. UNICEF has over 12,000 staff in more than 145 countries

Consultancy Title: Data Scientist Consultancy

Division/Duty Station: Health and HIV Unit/Data & Analytics/DAMP

Duration: November 1, 2025 – October 30, 2026

Home/ Office Based: Remote

BACKGROUND

Purpose of Activity/ Assignment:

UNICEF’s Data and Analytics team for Maternal, Newborn, Child, and Adolescent Health (MNCAH) plays a central role in strengthening global accountability and supporting countries to use data for better health outcomes. The team leads the development of global results frameworks, maintains the UNICEF MNCAH Global Database, and provides direct technical support to countries to improve data quality, analysis, and use.

A core pillar of this work is the Actionable Health Analytics for Decision-making (AHEAD) initiative, which aims to improve how routine health data is used across all levels of the health system. Through rapid-cycle analytics and tailored tools, AHEAD helps countries generate timely, subnational insights to guide policy and programming. It also supports improvements in data systems, coordination mechanisms, and country capacity for data-driven decision-making.

This consultancy, which will be hosted on the UNICEF-DRP GitHub, delivers a technology suite that takes outputs and figures from R scripts and makes them accessible to large language models (LLMs) for natural language querying. This approach ensures interoperability with cross-unit workflows, allowing various teams to leverage the tool regardless of their specific R script outputs. By transforming raw data into easily digestible insights, this work directly supports the Africa Data Strategy's shift "From Data to Insights," making data more accessible and useful for decision-making across the continent. This not only enhances technical assistance by improving data analysis capacity but also promotes knowledge exchange by fostering a shared, technology-driven approach to understanding child welfare data.

To support this growing portfolio, UNICEF is seeking support to:

• Strengthen global data infrastructure, analytics tools, and documentation of best practices

• Provide technical support to country offices and ministries of health to access, clean, and analyze routine data
• Finalize and scale country-specific data pipelines, dashboards, and analytics products

This role will be embedded within the MNCAH Data and Analytics team and will work closely with regional and country teams. The consultant will help close the gap between data and action, supporting more agile, accountable, and equitable health systems.

Scope of Work:

Under the supervision of the Statistics and Monitoring Adviser (MNCAH) and in close collaboration with UNICEF headquarters, regional offices, and country teams, the consultant will support the continued development and scale-up of data systems and analytics under UNICEF’s AHEAD (Actionable Health Analytics for Local Decision-making) initiative and the broader MNCAH data portfolio.

This role will contribute to strengthening country capacity to generate and use timely, high-quality data for decision-making, particularly to monitor and improve primary healthcare performance. The work will bridge advanced data methods with practical, country-facing tools that support public health planning and accountability.

1. Country Support and Operationalization

• Collaborate with country offices and ministries of health to access, clean, and analyze RHIS and administrative data, with a focus on supporting PHC and MNCAH planning.
• Customize country-specific analytics pipelines and visualizations to meet national and subnational decision-making needs.
• Contribute to country workshops, data interpretation sessions, and the preparation of evidence-based briefs and action plans.
• Translate analytics into real-world public health use cases (e.g., district performance tracking, service bottleneck identification, facility readiness monitoring).

2. Pipeline Development and Automation  

• Design and maintain automated, scalable data pipelines to ingest, transform, and standardize data from diverse sources, including DHIS2, MICS, WorldPop, and administrative datasets.
• Operationalize core analytics functions, including coverage estimation, indicator computation, geospatial integration, and data quality checks.
• Build and modularize pipeline components to ensure reusability across countries and alignment with rapid-cycle analytics needs.

3. Visualization and User-Centered Outputs

• Develop tailored outputs—such as dashboards, slide decks, and summaries—for use in country reviews, planning meetings, and supervision visits.
• Optimize visualization workflows for reproducibility, speed, and modularity, with a focus on administrative levels, health facilities, and thematic indicators.
• Design simple user interfaces (e.g., using Streamlit or Shiny) to allow non-technical users to run core analytics and generate outputs independently.

4. Global Infrastructure and Data Governance

• Support maintenance and expansion of the MNCAH Global Database and related data infrastructure, including automation and optimization of regular data refreshes.
• Implement metadata tracking, version control, audit trails, and internal monitoring tools for datasets, scripts, and outputs.
• Ensure data integrity and harmonization across indicators, geographies, and time periods

5. AI-Supported Analytics and Automation

• Develop a technology suite that takes outputs and figures from R scripts and makes them accessible to large language models (LLMs) for natural language querying
• Contribute to the integration of large language models (LLMs) and other AI tools into the AHEAD analytics package to streamline slide generation, narrative development, and structured summaries.
• Support the refinement of prompting, caching, and logic to ensure outputs are context-appropriate, locally relevant, and cost-effective.
• Collaborate with the fractional AI engineering team to embed verified data and local interpretation into country-specific products.

6. Reproducibility, Documentation, and Capacity Strengthening

• Ensure that all workflows are version-controlled, reproducible, and documented with clear metadata and standardized formats.
• Produce internal manuals and guides to support ongoing maintenance and scale-up of AHEAD tools.
• Conduct regular handover sessions and contribute to technical briefings, proposal development, and team onboarding materials to build institutional capacity and sustainability

Terms of Reference / Key Deliverables:

Work Assignment Overview/Outputs as per TOR/Deliverable/ Delivery deadline

1.  Pipeline Development and Automation

-  Non-facility data is integrated into the database and reliably available for analysis.

Integrated database with non facility data

30 Nov 2025

-  New data sources can be onboarded quickly via scalable modules

At least 5 new data sources onboarded

31 Dec 2025

-  Geospatial layers are incorporated into the database, enabling population-based analysis

Database incorporated with geospatial data

31 Jan 2026

-  Coverage metrics are produced faster and more robustly using optimized numerator/denominator pulls

Coverage metrics using optimized numerator /denominator pulls

28 Feb 2026

-  Emerging datasets (HIV, climate, HR, conflict) are added as needed to keep analyses current and comprehensive

HIV, climate, HR, conflict Integrated datasets added

31 Mar 2026

-  Data quality issues are automatically detected and  surfaced, with transparent review of imputations and outliers

A system in place for automatic detection of data quality and imputations

30 Apr 2026

2.  AI-Supported Analytics and Automation (Technology Suite for LLMs)

-  The AI prompting backend moved to Python stack, improving reliability and maintainability

Python based AI prompting backend

31 May 2026

-  Prompting performance is optimized (caching/parallelization), reducing cost and latency at scale

Optimized prompting performance

30 Jun 2026

3.  Visualization and User-Centered Outputs

-  Analysis outputs across different admin, facility, and grid levels are reproducible, fault-tolerant, and measurably faster

Reproducible analysis outputs at different levels

31 Jul 2026

-  Visualizations are consistent and reusable, accelerating analyst turnaround

Reusable visualizations in PowerPoint format

30 Aug 2026

4.  Reproducibility, Documentation, and Capacity Strengthening

-  ETL, AI query, and output generation status is monitored with timely alerts to prevent delivery delays

Timely alerts set up for monitoring

30 Sept 2026

-  Versioned documentation provides auditable methods, data models, and prompting standards as they evolve

A report with full documentation of different versions

31 Oct 2026

Qualifications

Education:

• A bachelor’s degree in Data Science, Statistics, Computer Science, Epidemiology, Public Health, Engineering, Health Informatics, or a related quantitative field.
• Additional certifications or training in data engineering, data visualization, or advanced statistical methods using R is an asset.

Knowledge/Expertise/Skills required *:

Professional Experience:

• A minimum of 5 years of progressively responsible professional experience in data science, data engineering, or health data analytics especially MNCAH data, with proven experience applying advanced data techniques to public health or development contexts.
• Demonstrated experience in:
• Designing and maintaining reproducible data pipelines and automated reporting tools using R.
• Handling large, complex datasets, particularly routine health information system (RHIS) data (e.g., DHIS2), administrative datasets, or survey data (e.g., DHS, MICS).
• Developing statistical models and conducting data quality assessments (e.g., imputation, outlier detection, validation).
• Building interactive dashboards and data visualizations using R or Python packages.
• Supporting version control workflows using GitHub, GitLab, or other collaborative platforms.
• Experience supporting decision-makers in the use of data for decision-making, particularly in low- and middle-income countries.
• Excellent written and oral communication of technical content in English. Proficiency in another UN language is highly desirable.
• Familiarity with global health indicator frameworks, especially those related to maternal health, newborn health, child health, primary health care, and health systems performance.

Additional Desirable Experience:

• Experience working with cloud-based database systems (e.g., Azure Postgres, AWS RDS) and building ETL pipelines that integrate geospatial and facility-level data.
• Understanding of data governance, privacy, and ethical use of health data.
• Proven ability to work in a multicultural, interdisciplinary team and coordinate across HQ, regional, and country levels.
• Prior experience contributing to capacity-building efforts through trainings, documentation, or mentoring is a strong asset.

The application to be submitted through the online portal should contain three separate attachments:   

• A Cover letter explaining the motivation for applying and explaining how the qualifications and skillset of the candidate   
• Curriculum Vitae (CV)   
• A financial proposal indicating professional fee as per the above template. Please do not forget to specify your name in the file while saving. (To be uploaded under other supporting documents).  

Requirements:

Completed profile in UNICEF's e-Recruitment system and

- Upload copy of academic credentials

- Financial proposal that will include/ reflect :

• • the costs per each deliverable and the total lump-sum for the whole assignment (in US$) to undertake the terms of reference.
  • travel costs and daily subsistence allowance, if internationally recruited or travel is required as per TOR.
  • Any other estimated costs: visa, health insurance, and living costs as applicable.
  • Indicate your availability

- Any emergent / unforeseen duty travel and related expenses will be covered by UNICEF.

- At the time the contract is awarded, the selected candidate must have in place current health insurance coverage.

- Payment of professional fees will be based on submission of agreed satisfactory deliverables. UNICEF reserves the right to withhold payment in case the deliverables submitted are not up to the required standard or in case of delays in submitting the deliverables on the part of the consultant.

U.S. Visa information:

With the exception of the US Citizens, G4 Visa and Green Card holders, should the selected candidate and his/her household members reside in the United States under a different visa, the consultant and his/her household members are required to change their visa status to G4, and the consultant’s household members (spouse) will require an Employment Authorization Card (EAD) to be able to work, even if he/she was authorized to work under the visa held prior to switching to G4.  

Only shortlisted candidates will be contacted and advance to the next stage of the selection process

For every Child, you demonstrate…

UNICEF’s core values of Commitment, Diversity and Integrity and core competencies in Communication, Working with People and Drive for Results. View our competency framework at: Here

UNICEF offers reasonable accommodation for consultants/individual contractors with disabilities. This may include, for example, accessible software, travel assistance for missions or personal attendants. We encourage you to disclose your disability during your application in case you need reasonable accommodation during the selection process and afterwards in your assignment. 

UNICEF has a zero-tolerance policy on conduct that is incompatible with the aims and objectives of the United Nations and UNICEF, including sexual exploitation and abuse, sexual harassment, abuse of authority and discrimination. UNICEF also adheres to strict child safeguarding principles. All selected candidates will be expected to adhere to these standards and principles and will therefore undergo rigorous reference and background checks. Background checks will include the verification of academic credential(s) and employment history. Selected candidates may be required to provide additional information to conduct a background check. 

Remarks:  

Individuals engaged under a consultancy will not be considered “staff members” under the Staff Regulations and Rules of the United Nations and UNICEF’s policies and procedures and will not be entitled to benefits provided therein (such as leave entitlements and medical insurance coverage). Their conditions of service will be governed by their contract and the General Conditions of Contracts for the Services of Consultants. Consultants are responsible for determining their tax liabilities and for the payment of any taxes and/or duties, in accordance with local or other applicable laws. 

The selected candidate is solely responsible to ensure that the visa (applicable) and health insurance required to perform the duties of the contract are valid for the entire period of the contract. Selected candidates are subject to confirmation of fully-vaccinated status against SARS-CoV-2 (Covid-19) with a World Health Organization (WHO)-endorsed vaccine, which must be met prior to taking up the assignment. It does not apply to consultants who will work remotely and are not expected to work on or visit UNICEF premises, programme delivery locations or directly interact with communities UNICEF works with, nor to travel to perform functions for UNICEF for the duration of their consultancy contracts. 

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