Small-Area Estimation & Data Fusion · Survey Methodology · Statistical Software
Twenty years of small-area estimation, survey methodology, and official statistics: from the WHO/UNICEF immunization estimates for 195 countries to county-level health estimates across all 102 Illinois counties. I consult through Samplics LLC, and every number I deliver can be re-run from its inputs.
import svy design = svy.Design(stratum="sdmvstra", psu="sdmvpsu", wgt="wtmec2yr") sample = svy.Sample(data=nhanes, design=design) # mean SBP among adults with diabetes, by age group sbp = sample.estimation.mean( y="sys_bp", by="age_group", domain="diabetes == 1", )
About
I'm Mamadou S. Diallo, a Ph.D. statistician based in Hoboken, NJ. For two decades I've turned sparse, multi-source data into defensible local estimates: small-area estimation, survey methodology, and the integration of survey, administrative, census, and geospatial data, across immunization, HIV, chronic disease, and official statistics.
Lead sampling statistician on the Population-based HIV Impact Assessment surveys (8 countries, with CDC/PEPFAR). Directed the WHO/UNICEF immunization estimates (WUENIC) for 195 countries at UNICEF, and developed sampling methodology for Statistics Canada's national health surveillance system (CCHS) earlier in my career. Author of Samplics (280K+ downloads, JOSS) and architect of the open-source svy ecosystem.
I also build the infrastructure evidence runs on. Solo architect of svyLab, a multi-tenant analytics platform with architectural sandbox isolation, lifecycle and classification governance, AI-assisted analysis with full provenance, and a 327-test invariant suite. Built so that survey-correct estimation is reproducible and auditable by construction: every result carries its model, code, weights, and CI.
My long-term goal is to modernize how survey data gets analyzed: open, reproducible, survey-correct tooling as a genuine alternative to SAS, SPSS, and Stata. The svy ecosystem and svyLab are open source and a career-long commitment — I maintain them the way statisticians maintain CRAN packages. Day to day I consult through Samplics LLC: sample design review, weighting and variance estimation, small-area estimation, and capacity building for statistics offices, health agencies, foundations, and research institutes. I am taking engagements for Q3/Q4 2026.
Ph.D. Statistics, Carleton University
(advisor: J.N.K. Rao)
M.Sc. Statistics, Université Laval
ASA (since 2010) · AAPOR
Guest Editor, JSSAM 2025
English & French: fluent in both speaking and writing
Hoboken, NJ: open to remote and on-site engagements
Taking engagements for Q3/Q4 2026: small-area estimation, survey design, weighting and variance estimation, and reproducible survey analysis.
Services
I work with health agencies, statistics offices, foundations, research institutes, and survey firms in defined engagements, each with a fixed scope and timeline. These are the six I take most often; if your problem sits between them, describe it and I'll scope it.
Independent review of a planned or in-field design: frame, stratification, sample size calculation and allocation, precision under realistic response. Written memo with prioritized, defensible recommendations.
Discuss this engagement →Base weights, nonresponse adjustment, calibration, and replicate or linearized variance estimation — delivered as documented, re-runnable code with a methodology annex fit for publication or audit.
Discuss this engagement →Subnational estimates for one priority indicator: Fay–Herriot, unit-level, or spatial Bayesian, with model diagnostics, uncertainty, and disclosure review. Scoped to prove the approach before committing to a programme.
Discuss this engagement →Sampling and statistical methodology sections for competitive bids, with named-personnel credentials and power calculations. Built for firms responding to federal or multilateral solicitations on deadline.
Discuss this engagement →Workshops for statistics offices and research teams: sampling design, weighting, small-area estimation, reproducible survey analysis in Python or R. Delivered in English or French.
Discuss this engagement →Two to three days per week inside a team to unblock a live estimation workstream, or to hold methodological continuity during a hire.
Discuss this engagement →Every engagement is defined in writing before it starts — deliverable, timeline, fee — and every number delivered can be re-run from its inputs.
That last part is not a promise, it's infrastructure. I wrote Samplics (280K+ downloads, JOSS), the reference Python library for survey statistics, and I build svyLab, where every result persists with its model, code, weights, and CI. Clients get documented, re-runnable code — not a spreadsheet of final numbers.
Selected work
A selection of the platforms I've built, the methods I've developed, and the population-based studies that ground both.
At NORC, developed the statistical analytical engine behind the Healthy Illinois Analytics Platform, producing county- and community-level health estimates across all 102 Illinois counties using small area estimation. Integrated American Community Survey administrative data with survey microdata under disclosure control.
At UNICEF, led the annual production of WHO/UNICEF immunization coverage estimates for 14 vaccines across all 195 countries. Integrated administrative reporting (DHIS2), household-survey microdata (DHS, MICS), and programme surveillance under GATHER reporting standards, with fit-for-purpose assessments across data modalities.
Production-grade Python library for sample selection, weighting, estimation, and small area estimation. Published in the Journal of Open-Source Software (JOSS, 2021). The reference implementation for survey statistics in Python.
JOSS paper →At Westat, developed model-based small area estimation for state- and county-level crime rates using 15 years of National Crime Victimization Survey data. Published the R package sae2 on CRAN, used for federal subnational statistics.
Lead sampling statistician at Westat for the Population-based HIV Impact Assessment surveys across Cameroon, Côte d'Ivoire, Malawi, Namibia, Tanzania, Uganda, Zambia, Zimbabwe, in collaboration with ICAP at Columbia and CDC/PEPFAR. Multi-stage probability samples for HIV prevalence, incidence, viral-load suppression, and ART coverage at national and subnational levels.
Sole architect and developer of a multi-tenant analytics platform for health-data evidence generation: architectural sandbox isolation, lifecycle and classification governance with audit logs, and AI-assisted analysis where every output persists with full provenance — model, prompt, code, tokens, cost, timestamp. 327 passing tests including cross-org sandbox enforcement and existence-leak contracts. This is the infrastructure behind the reproducibility guarantee on my engagements.
Platform deep-dive →Survey-weighted causal inference: IPTW, stabilized weights, and doubly robust estimation extending design-based survey methods to causal and transportability questions, validated against NHANES. Methods paper in preparation.
Publications
Peer-reviewed work in observational and survey methodology, small area estimation, population health, and machine learning.
Get in touch
I consult through Samplics LLC on sample design, weighting and variance estimation, small-area estimation, and statistical capacity building — for statistics offices, health agencies, foundations, research institutes, and firms bidding on federal or multilateral solicitations. Taking engagements for Q3/Q4 2026, remote or on-site, in English or French.
Tell me what you're trying to estimate and by when. If it's a fit I'll come back with a scope, a timeline, and a fee; if it isn't, I'll say so. I respond to all inquiries within two business days.
I also consider senior roles in survey methodology, small-area estimation, and population-health measurement.
Consulting one-pager (PDF)Engagements, methods, and selected work on one page. Full CV available if you need it.
I'll respond within two business days.