Kampala, Uganda. Open to remote and international work.
Data scientist and ML engineer
Johnson Mugarra
Six years turning field data into evidence across East Africa and the Horn of Africa. Today that means evaluation research for private companies, UN agencies and international NGOs, and the data systems behind the vanilla and coffee value chains at Enimiro. Earlier in my career I ran evaluations of health programs for USAID SITES, and built the vanilla harvest forecasting model for Uganda's Ministry of Agriculture (MAAIF).
- In the field
- 6+ yrs
- Organizations served
- 15+
- Peer-reviewed papers
- 2
- Vanilla
- Harvest timing research, field and climate data
- Evaluations
- Design, data collection, analysis and reporting
- Data systems
- Quality checks during daily collection
- Farmer data
- Pipelines and dashboards at Enimiro
Organizations I have worked with
Background
I began in management consulting at Bronkar Uganda, conducting impact evaluations, developing workplans, research designs, survey tools, field research, and analysis for client studies. From there I moved into evaluation research for non-profits, working on field assessments and survey work in Uganda.
The questions that mattered most in that work were causal ones: whether a program changed an outcome, or whether the outcome would have moved anyway. Answering that properly needs more than descriptive statistics, which is what took me to the M.Sc. in Data Science: machine learning, natural language processing, computer vision and Bayesian inference, with enough time on each to understand what the standard implementations are doing underneath.
At USAID SITES I supported qualitative field research for health system studies, with deployments concentrated in Eastern and Northern Uganda, including facility readiness work for Health Information Exchange and review of electronic medical records against ART registers. Over the same period, with MAAIF and Makerere, I researched vanilla maturity and harvest timing using field measurements and climate data.
At Enimiro I maintain the farmer data system, pipelines, and dashboards. Before that, at the Center for Research and Communication, I coordinated proposals and provided technical input for evaluations covering design, sampling, tools, analysis, and reporting. Certified in Power BI, SAS, Tableau and Google project management.
Methods
Machine learning, NLP, computer vision and Bayesian inference, from the statistics underneath to a model running in production.
Recent work
Harvest forecasting, evaluation cycles cut from six weeks to ten days, and data-quality checks built into daily collection.
Certification standards
Exporters answer to certification bodies like Control Union and Rainforest Alliance. Their standards call for records an auditor can trace from plot to shipment.
Publications
Co-author on two peer-reviewed papers in Agronomy and Advances in Agriculture.
Experience
-
November 2025 to September 2026
Research and Data Consultant
Enimiro Products Uganda Ltd, Kayunga, Uganda
Coordinate with the data team to collect, clean, and organize operational data on farming, production, sales, and sustainability. Maintain the Python pipeline from SurveyCTO into PostgreSQL with exports for dashboards, keep the farmer master auditable, and turn analysis into training material and management reports.
-
January 2025 to June 2026
Technical Lead Consultant
Center for Research and Communication (CRC), Remote
Coordinate proposals through writing and review of methods and work plans. Lead the technical work on evaluations including the IRC MERP endline, IRC baseline studies, the SOS Baidoa study, and UNICEF behavior change and awareness studies, covering design, sampling, tools, data quality, analysis, and report drafting.
-
January 2024 to June 2025
Researcher and Data Scientist, Vanilla Research
Makerere University with MAAIF, CRS, and private partners, Uganda
Researched vanilla maturity and harvest timing with supervisors in horticulture and statistics. Combined field measurements with satellite climate data and time-series models, applied thermal-time analysis, and helped establish the Kabanyolo demonstration plot. Work concluded with program funding closure.
-
February 2023 to November 2023
Research Associate
Innovations for Poverty Action (IPA), Kampala, Uganda
Supported process evaluation plans, survey instruments and computer-assisted interviewing, evaluation logistics and data cleaning, enumerator audits and quality checks, and reporting to partners.
-
July 2023 to March 2024
Qualitative Research Associate
Social and Scientific Systems for USAID SITES, Uganda
Short-term field research with deployments concentrated in Eastern and Northern Uganda. Assessed facility readiness for Health Information Exchange and paperless viral load requests, comparing UgandaEMR records with ART registers and cards, and prepared activity reports with safe handling of data.
-
September 2021 to January 2023
Research Associate
Bronkar (U) Limited, Kampala, Uganda
Developed workplans, methods, and survey tools, trained enumerators, took part in field research, and cleaned and analyzed data for client reports and proposals.
Now
-
February 2026
Project management
Delivered the IRC MERP endline to its donor, funded by GFFO. Project management for the UNICEF community awareness work on the WASH SBC project is now under way.
-
January 2026
Data systems
Setting up data infrastructure and improving the data systems used day to day. The work covers field collection, checks, and storage.
Projects
-
Featured
- Python
- Prophet
- NASA POWER API
Vanilla supply chain predictive analytics
- Field and climate
- Data combined
- Policy input
- Harvest timing
Forecasting work built on satellite climate data, ground measurements and market prices to inform harvest timing discussions with MAAIF.
-
- Python
- Airflow
- PostgreSQL
Automated impact evaluation pipeline
- Shorter cycles
- Structured reporting
- Quality checks
- Built into collection
Python and Airflow pipeline covering ingestion, modeling and report generation with consistent quality checks.
-
- Prophet
- ARIMA
- R
Hierarchical time-series forecasting
Hierarchical forecasting with Prophet and ARIMA for Ugandan vanilla yields. This is the method underneath the MAAIF harvest model, and what I presented at the national forum.
-
CRC
- SurveyCTO
- R
- Power BI
Program evaluations for humanitarian clients
- Selected studies
- Across sectors
- Inception to reporting
- Scope of each study
Data support for surveys and needs assessments including tool design, field data collection, quality checks, analysis, and final reports. Includes work on the IRC MERP endline survey.
-
- SurveyCTO
- SQL
- Power BI
Malaria and HIV program evaluation
- Field research
- Eastern and Northern Uganda
- Health systems
- Facility assessments
With USAID SITES and health partners, supported facility readiness assessments for Health Information Exchange and paperless viral load requests, including review of UgandaEMR records against ART registers and cards in Eastern and Northern facilities.
-
MSc capstone
- Python
- NLP
- Network analysis
Social-media sentiment and information flow
MSc Data Science capstone at MAHE. Sentiment analysis of social-media posts, plus a network model with users as nodes and their interactions as edges, to study how information spreads across the graph.
-
MSc capstone
- Python
- Computer vision
- Deep learning
Gesture and object recognition
MSc Data Science capstone at MAHE. Machine perception for robotics: reading hand gestures such as a thumbs-up and recognizing objects from a camera feed, so a machine can work out what's in front of it.
-
Enimiro
- Python
- scikit-learn
- Random forest
Vanilla yield estimation model
- 101 kg
- MAE, against a 158 kg baseline
- 14
- Farm features
Random-forest model predicting recorded harvest for 275 surveyed farmers, validated out-of-fold. It beats the median baseline by cutting MAE from 158 kg to 101 kg. Certification status, land size and plant count carry the most signal.
-
Enimiro
- Python
- PostgreSQL
- Prophet
Farm data and analytics platform
- 7
- Automated pipelines
- Python + R
- Orchestrated
Seven scheduled jobs keep it running: moving field forms into a central database, pulling satellite weather records, refreshing harvest forecasts, and tracking purchases, pollination and quality inspections. All of it feeds Power BI and Looker dashboards.
-
Enimiro
- GeoPandas
- Folium
- GeoJSON
Farmer plot geomapping
Turned GPS plot boundaries into interactive district maps for agrohub planning in Kayunga, Rubirizi and other districts: static grids for print, and browsable HTML maps of farmer plots for the field teams.
-
Enimiro
- Python
- R
- Anker method
Vanilla farmer living income study
- 212
- Farmers surveyed
- 485
- Variables cleaned
Measured the gap between what vanilla farmers earn and a living-income benchmark, using Anker and Fairtrade reference values. A modular Python and R pipeline cleaned 485 survey columns into an analysis-ready dataset and a written study.
-
Enimiro
- Survey design
- Python
- Reporting
Kayunga agrohub needs assessment
Designed and analyzed a farmer needs assessment for a planned agrohub in Kayunga, covering who was surveyed, vanilla production, income and the challenges farmers named, written up as a report for management.
112 Use the arrows or swipe to move between projects
Live analytics
Agricultural analytics · illustrative simulation
Vanilla harvest season model
A simulated cohort of 1,000 vanilla farmers, calibrated to Uganda's real pollination and harvest calendar (January 2024 to June 2026). Vanilla beans take roughly 9 months to mature after hand-pollination, so the harvest line is the pollination curve shifted forward by 9 months. The main pollination season (September to November) drives the June and July main harvest; the secondary season (February to May) drives the December and January harvest.
- Main harvest window (Jun to Jul)
- Secondary harvest (Dec to Jan)
- Pollination activity
- Projected harvest (t+9 months)
Financial analytics · synthetic data
Transaction fraud detection model
Gradient-boosted risk scores across 2,000 synthetic bank transactions. Each point sits at its predicted risk score against transaction amount on a log scale, and the clustering shows how the model separates ordinary behavior from suspicious and confirmed fraud. The dashed vertical line marks the 0.50 classification threshold.
- Legitimate
- Suspicious
- Confirmed fraud
- Threshold 0.50
Skills and sectors
Sectors
- Agriculture and food security
- Education
- Public health
- Malaria and HIV programs
- Health information systems (DHIS2 and EMR)
- Refugee livelihoods
- SRHR and GBV social norms
- Humanitarian response
- Household living income
- Climate
Tools and where they were used
- Python
- The vanilla forecasting stack at MAAIF, the 7 Enimiro pipelines, and the random-forest yield model.
- R
- Evaluation analysis at CRC, and the living income study against Anker benchmarks.
- SQL and PostgreSQL
- The Enimiro farmer data warehouse and structured quality checks during collection and review.
- Prophet and ARIMA
- Hierarchical harvest forecasts combining field and climate inputs.
- Airflow
- Scheduling data pipelines with consistent checks and reporting.
- Power BI and Looker
- Dashboards for teams at USAID SITES and Enimiro. Microsoft-certified Data Analyst Associate.
- SurveyCTO and ODK
- Field data collection for evaluations across Somalia and the Horn of Africa, and for every Enimiro farmer survey.
- GeoPandas and Folium
- District plot maps for agrohub planning in Kayunga and Rubirizi.
- Causal inference
- Impact and endline evaluations for IRC, UNICEF, World Vision, Save the Children and others.
Other tools
From the MSc, applied in capstone projects
- Machine learning
- NLP
- Computer vision
- Bayesian inference
Visualisation
- D3.js (the 2 live charts on this page)
- Tableau (certified)
- Looker Studio
Workflow
- Git and GitHub
Let's talk about a project
- Emailjohnsonmugarra@yahoo.com
- Phone+256 702 860 815
- GitHubgithub.com/MugarraJohnson
- LocationKampala, Central Region, Uganda
Testimonials
-
"Johnson's forecasts changed how we plan. He combined satellite data with our field measurements, and the results went straight into briefings at the highest levels of government."
Senior Research LeadMAAIF / Makerere University
-
"The pipeline Johnson built took our evaluation process from six weeks to under ten days. Our USAID reports now go out on schedule, with data we don't have to re-check."
Director of ResearchCenter for Research and Communication
-
"He understands qualitative and quantitative research. Johnson's thought process when tackling complex projects is both methodical and innovative."
SupervisorBronkar
Publications and presentations
-
Unravelling Yield and Yield-Related Traits in Soybean Using GGE Biplot and Path Analysis
Agronomy (MDPI) · 2024 · Vol. 14, Art. 2826 · Open access
Co-authored study evaluating the yield and stability of 12 elite soybean varieties across 5 production areas in Uganda, using GGE biplot and path analysis to identify the traits that improve yield in tropical breeding programs.
- Peer-reviewed
- Statistical modeling
- Agronomy
-
Identifying Optimal Lines for Enhanced Symbiotic Performance in a Mini-Core Collection of Cowpea
Advances in Agriculture (Wiley) · 2025 · Open access
Co-authored study screening a mini-core cowpea collection for nitrogen fixation and symbiotic performance, applying statistical analysis to select superior genotypes for field evaluation across Ugandan agro-ecologies.
- Peer-reviewed
- Data analysis
- Agronomy
-
National forum presentation on agricultural analytics
Makerere University
Presented vanilla supply-chain research combining satellite and ground data with recommendations for agricultural policy.
- ML / AI
- Policy input
- Agriculture
-
Impact evaluation workshop
CRC Studies · 2025 · workshops for evaluation teams
Ran technical workshops for evaluation teams running studies in Somalia, covering study design and causal inference so the findings hold up as evidence.
- Training
- Impact evaluation
- Somalia
14 Use the arrows or swipe through publications
Education and certifications
Education
Certifications
-
Project Management
Google certified
Professional Certificate
-
Power BI
Microsoft certified
Data Analyst Associate
-
SAS Statistics
SAS Institute
Statistical Business Analyst
-
Tableau
Tableau / Salesforce
Desktop Specialist
Beyond work
-
Chess
I play slow games of chess. Each move has to be justified, and the board shows straight away when it was not.
-
Five-a-side football
I play five-a-side around Kampala at weekends. The game rewards players who see the next pass before it opens.
-
Arsenal FC
I have supported Arsenal for years, through rebuilds and title races.