Statistical Modelling Consultant, Data and Analytics

Overview Consultancy: Statistical Modelling Consultant Duty Station: Data and Analytics, DAPM Duration: February 1, 2026 – May 31, 2026 Home/ Office Based: Remote About UNICEF: If you are a committed, creative professional and are passionate about making a lasting difference for children, UNICEF invites you to apply. UNICEF operates in 190 countries and territories and focuses on child survival, protection and development. UNICEF is funded by voluntary contributions and has over 12,000 staff in more than 145 countries. Background: The MNCAH portfolio of the Data and Analytics Section at UNICEF New York maintains the global MNCAH database, a key source for country- and regional-level data used in SDG monitoring, program planning, and policy advocacy. The MNCAH team is expanding the database to align with emerging priorities, incorporating administrative, modeled, and subnational data. This consultancy will support maintenance and development of data products and reporting processes related to MNCAH (e.g., SDG monitoring, Strategic Plan reporting). Scope Of Work Under supervision of the Statistical and Monitoring Specialist (MNCAH), the consultancy will advance estimation processes including methodology, toolset, estimates and validation approaches. The scope includes: • Model Review and Development: Review existing modelling approach and finalize recommendations on temporal structures, short-term deviations, autocorrelation structures (AR(1)/ARMA), and hierarchical random effects. Compare time-only models, covariate-driven models, and multi-source models for different indicators and data contexts. Implement systematic covariate selection strategies, including Bayesian shrinkage (horseshoe priors) and hybrid methods (e.g., LASSO followed by Bayesian estimation). • Scaling & Validation: Extend framework to handle data-rich and data-sparse indicators, explore random-walk and intervention-sensitive models, develop rigorous validation strategies (out-of-sample prediction, sensitivity analysis, performance comparisons), and recommend suitable model specifications for each MNCAH indicator. • Framework & Codebase: Convert JAGS models to brms/cmdstanr on Databricks; refactor code into a modular, reusable structure with estimation, prediction, and visualization components; develop a visualization toolkit for country-level estimates and model diagnostics; set up a structured GitHub repository with documentation and vignettes. • Documentation & Reporting: Document methodological decisions, produce country-level profiles, and prepare a final technical report with methods, validation results, limitations, and recommendations. Indicators And Deliverables The following indicators are under consideration for modelling; subject to change based on programmatic decisions. The list includes maternal health, newborn health, child health, adolescent health, and data quality indicators. Documentation may include a table of candidate covariates with rationale and recommendations, and a timeline for deliverables. Work Plan & Deliverables Timeline Deliverables are organized by dates (examples): • Feb 28, 2026: Review modelling strategies, convert JAGS models, covariate selection and evaluation; initial Bayesian model implementations; technical note on comparative approaches. • Feb–Mar 2026: Refactor modelling scripts; extension to sparse vs rich datasets; empirical validation. • Mar 31, 2026: Develop visualization toolkit; production of country-level outputs; documentation and codebase finalization. • Apr 30, 2026: Synthesis and recommendations; technical summary; country profiles; structured GitHub repository. • May 31, 2026: Final dissemination of codebase and outputs; reusable plotting utilities for estimates and diagnostics. Qualifications Education: Masters in biostatistics, statistics, public health, or related discipline Knowledge/Experience: • At least 4 years of experience in statistical modelling • Demonstrated expertise with Bayesian methods and modelling • Proficiency in R programming; ability to code independently and resolve issues • Ability to work remotely and independently; high accuracy and attention to detail • Knowledge of maternal, neonatal, and child health data modelling challenges • Proficiency in English to clearly convey complex topics Requirements Completed profile in UNICEF's e-Recruitment system. Include: • Copy of academic credentials • Financial proposal detailing costs per deliverable and total lump-sum (USD) • Travel costs and per diem if applicable • Other estimated costs (visa, health insurance, living costs) • Availability Note: UNICEF may cover emergent duty travel; selected candidate must have health insurance and be fully vaccinated against SARS-CoV-2, where applicable. Additional Information U.S. Visa Information: Instructions vary by visa type; see policy details. Shortlisted candidates will be contacted. UNICEF offers reasonable accommodation for consultants with disabilities. UNICEF maintains a zero-tolerance policy on exploitation, harassment and discrimination and requires background checks. Consultants are not staff members and are governed by their contract and UNICEF's General Conditions of Contracts for the Services of Consultants. Background checks may include verification of credentials and employment history. Remarks: Consultants are responsible for tax liabilities. Visa and health insurance requirements must be maintained for the contract duration. All selections are subject to verification and eligibility. Apply tot his job