Unicef CHAD · 3 hours ago
Statistical Modelling Consultant, Data and Analytics, DAPM, NYHQ, remote. Req# 590596
UNICEF is the world's leading children's rights organization, dedicated to making a lasting difference for children globally. The Statistical Modelling Consultant will develop and validate country-level hierarchical Bayesian models for maternal, newborn, child, and adolescent health indicators to enhance data reporting processes and support SDG monitoring.
Non-profit Organization Management
Responsibilities
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)
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 constraining models against empirical data, and flagging anomalous results
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
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
Qualification
Required
Masters in biostatistics, statistics, public health, or related discipline
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
Benefits
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.
UNICEF offers reasonable accommodation for consultants/individual contractors with disabilities.
Company
Unicef CHAD
UNICEF works in 190 countries and territories to protect the rights of every child.
Funding
Current Stage
Growth StageCompany data provided by crunchbase