aiman noman.

Aiman Noman

A Humanitarian Data Analyst · MSC DATA SCIENCE

Nine years across UNICEF, WHO, and more

Aiman Noman - Portrait
Aiman Noman
01 / About

A seasoned Information Management and Data Analysis professional.

Leveraging extensive experience in humanitarian and development contexts, I excel in transforming complex data into actionable insights.

Driven by a passion for social impact, I specialize in creating and maintaining advanced data infrastructures, ensuring the efficient delivery of aid to those in need, even in complex humanitarian contexts.

Having worked across field, country, regional and global levels, I bring a unique and practical understanding of how data moves through humanitarian systems, from field operations to strategic decision-making.

02 / Expertise

What I excel at.

Strong foundations in data infrastructure, visualization, and reproducible analysis, developed across emergency operations, regional coordination, and global programme support.

Data Visualization

Translating complex datasets into clear, purposeful visual products. Dashboards, factsheets, maps, and charts — each designed to support informed decisions across diverse stakeholders.

Analytical Engineering

Building reproducible pipelines in R and Python that process survey microdata across countries, apply consistent statistical methods, and produce standardized outputs that scale.

Information Architecture

Designing how data is captured, stored, validated, and delivered — from beneficiary databases in active emergencies to metadata structures for global data publishing.

Capacity & Context

Comfortable moving between emergency field operations and institutional headquarters. Experienced in training teams on data tools, aligning outputs with national priorities, and adapting methods to fit the resources and constraints of each context.

03 / Experience

A decade of impact.

Working across international organizations to deliver data-driven solutions in humanitarian contexts.

Dec 2025 – Present
UNICEF HQ

Data Analyst Consultant

Supporting the development of a reproducible R-based workflow for multi-country education factsheets, automating an analytics pipeline, and building Shiny dashboards for country-level exploration.

Sep 2024 – Dec 2025
WHO Africa

Data & Information Management Officer

Managed health data from multiple countries, created systems and workflows, and processed large datasets using Python and R. Deployed applications and services in MS Azure and MS Fabric.

Oct 2020 – Apr 2024
UNICEF Yemen

Information Management Officer

Supported WASH, Child Protection, and Education programmes. Extensively used Power BI and Tableau for dashboards. Generated GIS products and advanced form building using ODK and Kobo.

May 2019 – Oct 2020
IBTCI Yemen

Database & Reporting Officer

Performed data cleaning, aggregation, and quality control. Utilized Power BI and Tableau for data shaping. Led capacity building efforts for data collection and database management.

Education

MSc, Data Science

University of East London (Apr 2025)

BSc, Information Technology

Lebanese International University (Apr 2018)

Languages

English

Native or Bilingual Proficiency

Arabic

Native or Bilingual Proficiency

French

Working Knowledge

04 / Collaborators

I am proud to have worked with some of the best entities.

05 / Stack

The stack, in motion.

Everything between the raw data and the final product.

an
aiman.noman / stack
06 / Writing

Recent projects.

May 24, 2026

When being in school isn't enough

Age-grade alignment and foundational learning across 45 countries.

Read Post
Data Storytelling Survey Analysis UNICEF
May 17, 2026

When learning starts too late

Foundational reading skills across ~45 MICS6 countries—where learning starts, accelerates, and where inequality persists.

Read Post
Data Storytelling Reproducible Analysis UNICEF
May 4, 2026

A vaccine that prevents cancer

A data story on cervical cancer burden, HPV vaccine introduction and coverage, and screening and treatment gaps across the WHO African Region.

Read Post
Public Health Data Pack WHO
May 21, 2024

Decoding Online Shopping Behaviors

Building a predictive model to analyze user purchases using Python.

Read Post
Machine Learning Python
Yemen map showing humanitarian aid prioritization by district
May 20, 2024

Prioritization of Humanitarian Aid

Analyzing and prioritizing humanitarian aid in Yemen using R and spatial analysis.

Read Post
Spatial Analysis R
Contact

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