Health financing and governance
Facility decision space, reimbursement delays, and how devolved systems translate policy into actual care.
About Me
From the field
From the field
to the boardroom,
and into AI systems.
My name is Nichodemus Amollo. I grew up near Lake Victoria in Homa Bay, Western Kenya, where I learned to pay attention — to the weather, to the lake, to what people say and what they don’t. That instinct has served me well in data work.
I started at KEMRI managing oncology data. It taught me something that no methods course quite captures: data quality is a moral act. Every row is a person waiting for a diagnosis. That sense of responsibility has traveled with me into every job since.
Over eight years I have worked across the full research lifecycle — designing digital survey tools for communities without internet, building the SQL databases that receive the data, leading field teams of 50+ across three countries, and delivering the reports and dashboards that move funders and governments. I currently work with Georgetown University gui2de on health financial diaries and impact evaluations. I am also a part-time lecturer in Biostatistics at JOOUST and a candidate for an MSc in Biostatistics and Epidemiology.
What makes me useful is that I can operate at both ends. I can sit with a community health worker and explain why data completeness matters. Then walk into a boardroom and present the findings. That translation — between the field and the funder — is where I work best.
I’m also actively building expertise in AI systems and machine learning infrastructure—specifically how rigorous statistical thinking translates to production ML systems. My field experience with data quality, causal inference, and real-world constraints directly informs how I think about responsible AI system design. Georgetown work includes architecting ETL pipelines, designing R Shiny dashboards with predictive components, and mentoring analysts transitioning toward data engineering and ML work.
Outside of data: I keep goats and tend a kitchen garden in Homa Bay. There is something honest about agriculture — it keeps development work grounded in reality. I also love football, running, and long conversations over tea that go further than they were supposed to.
Currently
Lead Research Data Manager
Georgetown University gui2de · Remote
MSc Candidate — Biostatistics & Epidemiology
JOOUST · Final thesis stage · Expected graduation Dec 2026
Part-Time Lecturer — Biostatistics
JOOUST
At a Glance
📍 Nairobi, Kenya. Open to remote and on-site.
🗣️ English, Kiswahili, Dholuo
🏛️ NGO · Corporate · Research · Government
🎓 MSc Thesis: NCD financing, Kisumu County
📝 First-author paper forthcoming in BMC Public Health
📚 Co-authored publications in oncology and epidemiology
Outside Work
🐐 Goat farming — Homa Bay County
⚽ Football — watching and playing
🏃 Running & fitness
📚 Agricultural economics & development
🌍 Open governance & civic data
🤖 Staying current with AI & systems thinking
What drives the work
I believe data has a side — it either serves the people it was collected from, or it serves the institutions that collected it. My goal is always the former.
That shows up in how I approach M&E: not as a compliance checklist, but as a learning system. It shows up in how I train enumerators: I want them to understand why the question is structured the way it is, not just how to tap the screen. And it shows up in how I write reports: I want to change a decision, not demonstrate that I can run a regression.
I bring the same philosophy to AI systems: the systems we build encode decisions. They should be interpretable, fair, and accountable to the people they affect.
Research interests
NCDs in primary care
Hypertension and diabetes management, medicine continuity, and service delivery quality in rural settings.
Mixed-methods research
Using records, interviews, and operational data together to explain not just what failed, but why.
Implementation and community pathways
Designing practical interventions that fit community realities rather than importing solutions unchanged.
AI fairness and systems design
How to build responsible AI systems that account for real-world constraints, equity, and interpretability—especially in low-resource health settings.
Skills & Tools
Analytics & Stats
R
STATA
Python
SPSS
Data & Databases
SQL
PostgreSQL
DHIS2/KHIS
Excel
Data Collection
KoboToolbox
ODK
REDCap
SurveyCTO
BI & Reporting
Power BI
R Markdown
Quarto
Tableau
A few highlights
- Built real-time high-frequency check (HFC) systems in R and Stata across multi-country RCTs, catching data errors before they compound.
- Managed a field team of 50+ enumerators across Kenya, Uganda, and Tanzania, including remote coordination through the COVID-19 pandemic.
- Designed and digitised the M&E framework for a 1,535-site health programme: XLSForm coding through DHIS2 integration.
- First-author paper forthcoming in BMC Public Health on financing constraints and chronic NCD care in rural Kisumu.
- Co-authored oncology and epidemiology publications from KEMRI and university collaborations.
- Identified procurement inefficiencies that saved an estimated KES 20M+ through analysis alone.
Services
What I offer as a consultant, collaborator, or embedded team member:
Study Design & Protocol Development
Research question formulation, sampling strategy, ethical submissions, instrument design (quantitative & qualitative). IRB-ready protocols for health, agriculture, and finance programmes.
Data Management & Engineering
Database architecture, HFC systems, automated cleaning pipelines in R and Python. Reproducible data workflows that teams can hand off without losing institutional knowledge.
Analytics & Impact Evaluation
Descriptive to advanced econometrics — regression, DiD, RDD, survival analysis. Telling the story behind the numbers for funder reports, policy briefs, and publications.
Dashboards & Reporting
Automated dashboards in Power BI, R Shiny, and Quarto. From operational monitoring dashboards for field programmes to donor-facing KPI reports updated on a schedule.
ML Systems & Predictive Analytics
Building production-ready models grounded in statistical rigor. From feature engineering to model deployment, monitoring, and reproducible infrastructure. Focus on systems that work in real-world constraints.
Field Data Collection
End-to-end management of CAPI surveys — tool building in KoboToolbox / ODK, enumerator recruitment and training, daily HFC, and data transmission to headquarters.
Training & Capacity Building
Workshops in R, Stata, survey design, data management, M&E frameworks, and reproducible research. I have trained teams ranging from government statisticians to community health workers.
Get in touch about a project →
Open to
Senior M&E and Research Data Manager roles blending AI and data systems, data analytics consulting across supply chain, health, agriculture, finance and real estate, ML systems and predictive analytics work, research partnerships in health financing and agricultural economics, and training and capacity building in R, Stata, survey design, data management, and reproducible research practices.