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: Statistical Modelling Consultant

Duty Station: Data and Analytics, DAPM

Duration: February 1, 2026 – May 31, 2026

Home/ Office Based: Remote

 

BACKGROUND

Purpose of Activity/ Assignment:

The Maternal, Newborn, Child, and Adolescent Health (MNCAH) portfolio of the Data and Analytics Section of UNICEF New York Headquarters maintains and updates the global MNCAH database which is a key source for country- and regional-level MNCAH data. This database is used by a wide range of stakeholders for activities related to SDG monitoring, global, regional, and country programme planning, and policy advocacy. The MNCAH team is expanding the MNCAH database to align with the emerging global health landscape and priorities, incorporating administrative data, modeled data, and subnational data. This expansion will improve the timeliness and availability of the data, necessitating strategic enhancements to the global database workflow.  In addition to maintaining the global database, this consultancy will support maintenance and development of data products and data reporting processes such as SDG monitoring, Strategic Plan reporting, and other global reporting processes related to MNCAH.

The purpose of this assignment is to develop and validate country-level hierarchical Bayesian models for several MNCAH indicators for UNICEF’s reporting and monitoring. These models will evaluate the uncertainty and integrate data from country routine systems and survey data, provide annualized estimates for indicators at the country level, and forecast indicators within short time horizons.

Scope of Work:

Under the supervision and guidance of Statistical and Monitoring Specialist (MNCAH), the scope of the consultancy is to advance the estimation processes used by the MNCAH team, including developing the methodology, toolset, estimates, and validation approaches. The scope includes:

1. Model Review and Development

• Review the existing modelling approach and finalize recommendations on the temporal structures and short-term deviations, autocorrelation structures (AR(1)/ARMA), and hierarchical random effects.
• Compare time-only models, covariate-driven models, and multi-source models, assessing their suitability for different indicators and data contexts.
• Implement systematic covariate selection strategies, including Bayesian shrinkage (horseshoe priors) and hybrid methods (screening such as LASSO followed by Bayesian estimation).

2. Scaling & Validation

• Extend the modelling framework to handle both data-rich and data-sparse indicators, possibly through a dual or unified structure.
• Explore random-walk and intervention-sensitive models for indicators influenced by programmatic changes rather than covariate trends.
• Develop and apply rigorous validation strategies (out-of-sample prediction, sensitivity analysis, performance comparisons).
• Recommend the most suitable model specifications for each MNCAH indicator, ensuring adaptability across contexts.
• Identify a framework to evaluate model results, including constraing models against empirical data, and flagging anomalous results.

3. Codebase & Tools

• Convert existing JAGS models into brms/cmdstanr equivalents on Databricks to enhance efficiency, reproducibility, and integration with modern Bayesian workflows.
• Refactor existing code into a modular, reusable, and transparent codebase, including functions for estimation, prediction, and visualization.
• Develop a visualization toolkit with reusable plotting utilities for country-level estimates, raw data overlays, covariate diagnostics, and model performance plots.
• Set up a structured GitHub repository (or equivalent) with documented scripts, reproducible workflows, and annotated vignettes.

4. Documentation & Reporting

• Document all methodological decisions, assumptions, covariate treatment, and validation processes.
• Produce country-level profiles combining model outputs with annotated data sources and explanatory notes.
• Prepare a final technical report summarizing methods, validation results, limitations, and recommendations for future methodological development.

Indicators under consideration  

The following indicators are a base list of MNCAH indicaotrs to be considered in modelling but subject to make changes either addition or substraction based on programmatic decision.

Maternal health

• Proportion of pregnant women with at least one (1) antenatal care (ANC) contact in a facility
• Proportion of pregnant women with at least four (4) antenatal care (ANC) contacts in a facility
• Proportion of pregnant women with at least eight (8) antenatal care (ANC) contacts in a facility
• Proportion of pregnant women with first antenatal care (ANC) contact in a facility in the first trimester (up to 12 weeks of gestation)

• Percentage of women (aged 20-24 years) who gave birth before age 18. 

• Proportion of pregnant women screened for syphilis during ANC contact in a facility
• Proportion of women who gave birth in a health facility
• Proportion of women, aged 15–49, with a live birth attended by a skilled health personnel (doctors, nurses, or midwives) during delivery
• Proportion of deliveries in health facilities by caesarean section
• Proportion of women receiving postnatal care (PNC) in a facility within two (2) days after delivery
• Proportion of women who gave birth in a facility who received a prophylactic uterotonic (e.g. Oxytocin) immediately after birth for prevention of postpartum hemorrhage
• Proportion of women who delivered in a health facility and initiated or left with a modern contraceptive method prior to discharge

Newborn health

• Proportion of newborns receiving postnatal care (PNC) in a facility within two (2) days after delivery
• Proportion of births in facilities that are preterm (less than 37 weeks gestation)
• Proportion of live births in facilities with birthweight less than 2500 g
• Proportion of babies born (live births and stillbirths) in a health facility with birthweight documented

Child health

• Proportion of outpatient department visits per person per year among children under 5 years of age
• Proportion of children under 5 years of age presenting to a health facility with any sign of acute respiratory infection (ARI)
• Proportion of childhood (under 5 years) cases of pneumonia given/prescribed amoxicillin in health facilities
• Proportion of childhood cases (under 5 years) of diarrhoea given/prescribed treatment for diarrhoea in health facilities
• Percentage of children (under age 5) with diarrhoea who received ORT (oral rehydration salts or recommended homemade fluids or increased fluids) and continued feeding.
• Percentage of children (under age 5) with diarrhoea who received zinc.
• Percentage of children with diarrhoea receiving oral rehydration salts (ORS). 
• Percentage of children with diarrhoea receiving ORS and zinc.
• Percentage of women (aged 15-49 years) who received three or more doses of intermittent preventive treatment during antenatal care visits during their last pregnancy.
• Percentage of children (under age 5) with fever for whom advice or treatment was sought from a health facility or provider.

• Percentage of children in malaria-endemic countries sleeping under an insecticide-treated net. 
• Percentage of households with at least one ITN for every two persons and/or IRS in the past 12 months.
• Percentage of households with at least one insecticide-treated mosquito net (ITN).
• Pregnant women sleeping under ITN - percentage of pregnant women (aged 15-49 years) who slept under an insecticide-treated net the previous night.
• Percentage of febrile children (under age 5) who had a finger or heel stick for malaria testing.
• Percentage of febrile children (under age 5) receiving ACT (first line antimalarial drug), among those receiving any antimalarial drugs
• Proportion of children under 5 years diagnosed with malaria, confirmed by RDT or microscopy
• Proportion of children under five years presenting to a health facility who were diagnosed with malaria and received ACT (or other first-line treatment according to national policy)
• Proportion of hospitalised cases of injuries (e.g. road traffic injuries, fire-related burns, poisonings, falls, and drowning) among children under 5 years of age per 100 000 under-5 population during a year

Adolescent health

• Proportion of outpatient department visits per person per year among adolescents (10–19 years)
• Proportion of adolescents who accessed a health professional or counsellor for anxiety or depression
• Proportion of hospitalised cases of injuries (e.g. road traffic injuries, burns, poisonings, falls, drowning) among adolescents (10–19 years) per 100 000 adolescent population during a year
• Proportion of pregnant adolescents (10–19 years) with at least one (1) antenatal care (ANC) contact in a facility
• Proportion of adolescents (10–19 years) who gave birth in a health facility
• Proportion of new cases of specified sexually transmitted infections (STIs) (e.g., syphilis, gonorrhoea, chlamydia, HSV-2) among adolescents (10–19 years)

Data Quality

• Proportion of expected facility reports that are actually received

Terms of Reference / Key Deliverables:

Work Assignment Overview/Deliverables and Outputs/Delivery deadline

1.Review of modelling strategies for temporal structure and deviations, conversion of JAGS models to brms/cmdstanr and covariate selection and evaluation

• Technical note on comparative modelling approaches
• Initial Bayesian model implementations (time-only, covariate-driven, multi-source)
• Table of candidate covariates with rationale and recommendations

Feb 28, 2026 

2. Refactoring of modelling scripts

Extension to sparse vs rich datasets

Empirical model validation and comparison

• Reusable, modularized codebase with plotting functions
• Unified/dual framework for handling diverse data contexts
• Validation results and recommended models per indicator

March 31, 2026

3. Development of visualization toolkit

Methodological documentation

Production of country-level outputs

Finalization and dissemination of codebase

• Reusable plotting utilities for estimates, covariates, and diagnostics
• Technical report summarizing assumptions, methods, validation
• Country profiles with annotated data and model estimates
• Structured GitHub repository with documentation and vignettes

April 30, 2026

4.  Synthesis and recommendations

• Technical summary highlighting innovations, limitations, and next steps

May 31, 2026

Qualifications

Education:   

Masters in biostatistics, statistics, public health, or related discipline

Knowledge/Expertise/Skills required *:

• At least 4 years of experience in statistical modelling
• Demonstrated expertise with Bayesian statistical methods and modelling.
• Competence using R software programming including an ability to code and work independently investigating and resolving program bugs.
• Ability to work independently and efficiently whilst working remotely from other members of the team.
• Accuracy and attention to detail.
• Ability to produce high-quality outputs whilst working to short deadlines.
• Knowledge and understanding of key issues and modelling challenges for maternal, neonatal, and child health data.
• Proficiency in English sufficient to clearly convey complex technical topics to a lay audience

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.