UNICEF · 16 hours ago
Statistical Modelling Consultant, Data and Analytics, DAPM, NYHQ, remote. Req# 590596
United States
Full-time
Remote
Mid, Senior Level
4+ years expUNICEF is the world's leading children's rights organization, dedicated to promoting children's survival, protection, and development. They are seeking a Statistical Modelling Consultant to develop and validate country-level hierarchical Bayesian models for various maternal, newborn, child, and adolescent health indicators, enhancing the global MNCAH database and reporting processes.
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Responsibilities
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)
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 constraining models against empirical data, and flagging anomalous results
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
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
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
UNICEF works in some of the world’s toughest places, to reach the world’s most disadvantaged children. To save their lives. To defend their rights.
10001+ employees
H1B Sponsorship
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Funding
Current Stage
Late StageLeadership Team
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