Aggrey Ongweso
Data Analyst | Software Developer | Research Data Specialist | Statistical Analysis | Public Health Analytics | Data Visualization | Digital Health Technology
About Me
I am Aggrey Ongweso, a results-oriented data analyst, research data specialist, and software developer working at the intersection of data, public health research, technology, and software engineering.
My work combines data analytics and software development to transform raw data into reliable information, analytical insights, dashboards, digital tools, and practical technology solutions.
I work across the complete data lifecycle, from electronic data collection and database design to data cleaning, statistical analysis, visualization, application development, API development, and deployment of digital systems.
On the analytics side, I work with R, Stata, SAS, Python, SQL, Excel, Power BI, and Tableau. On the software development side, I build applications and data-driven systems using Python, FastAPI, React, JavaScript, HTML, CSS, Vite, Tailwind CSS, PostgreSQL, SQL Server, and REST APIs.
My portfolio demonstrates practical work in statistical analysis, antimicrobial resistance research, disease surveillance, data visualization, dashboards, electronic data collection, database development, web applications, APIs, and digital health technology.
Data Analytics & Research Expertise
- Data Management: cleaning, validation, restructuring, coding, quality assurance, data integration, and database preparation.
- Statistical Analysis: descriptive analysis, prevalence estimation, hypothesis testing, Fisher's exact tests, logistic regression, multivariable analysis, and epidemiological analysis.
- Research Data: epidemiological datasets, public health datasets, surveillance data, laboratory data, and longitudinal or repeated observations.
- Data Visualization: publication-ready charts, analytical reports, interactive dashboards, KPIs, and data storytelling.
- Digital Data Collection: ODK/XLSForm, REDCap, and KoBoToolbox, including form design, deployment, validation, data review, and iterative refinement.
- Database & Data Engineering: SQL querying, relational database design, PostgreSQL, SQL Server, data transformation, database preparation, and structured data pipelines.
- Reproducible Research: R scripts, Python workflows, R Markdown, structured analytical pipelines, and documented research workflows.
Software Development & Digital Health
Software development is an important part of my technical work. I develop data-driven applications that connect databases, APIs, analytical workflows, and user interfaces to solve practical research and public health problems.
- Frontend Development: HTML5, CSS3, JavaScript, React, Vite, responsive interfaces, component-based development, and Tailwind CSS.
- Backend Development: Python, FastAPI, RESTful APIs, application logic, authentication, data validation, and API integration.
- Database Development: PostgreSQL, SQL Server, relational database design, SQL queries, database relationships, and data management.
- Full-Stack Applications: development of complete applications connecting frontend interfaces, backend services, APIs, authentication systems, and databases.
- Data-Driven Applications: development of systems that integrate data collection, analysis, visualization, reporting, and decision support.
- Health Technology: development of disease surveillance systems, research data applications, health dashboards, and digital tools for public health workflows.
- AI & Computational Tools: development of AI-enabled interfaces and computational workflows for biological and public health data.
Software Development Projects
1. Disease Surveillance System
A data-driven disease surveillance application designed to support structured disease reporting, health data management, monitoring, and decision support.
The system architecture incorporates a React frontend, FastAPI backend, PostgreSQL database, REST APIs, authentication, and structured health data workflows.
2. PaanGenAI
A bioinformatics and AI-oriented software platform designed to provide users with tools for pathogen exploration, AI-assisted questions, sequence comparison, and biological data analysis.
The application incorporates a modern React interface, Vite-based development environment, reusable components, authentication workflows, file uploads, analytical pages, and an architecture designed to integrate computational and AI-based functionality.
3. GENA Initiative Platform
Designed and developed the GENA Initiative platform, a public-health and bioinformatics-oriented digital platform focused on open-source genomic science, artificial intelligence, data-driven research, and capacity building.
The platform provides an online presence for the GENA Initiative and presents its mission, research activities, technology focus, team, and initiatives aimed at connecting bioinformatics, AI, genomics, and public health.
4. Research Data Collection & Analysis Workflow
Developed an iterative workflow connecting electronic data collection with R-based data analysis. Analytical findings were used to identify issues in the data collection instrument, revise the form, redeploy the instrument, and improve subsequent data collection.
Selected Data, Research & Surveillance Projects
Worked within a Health and Demographic Surveillance System (HDSS) environment supporting the collection, management, processing, analysis, and reporting of longitudinal population and health data. The work involves handling demographic and health-related information generated through continuous population surveillance.
Experience includes working with structured surveillance datasets, data quality checks, data cleaning and management, variable creation, data analysis, reporting, and visualization. HDSS data provides an important foundation for understanding population dynamics, mortality, morbidity, migration, births, and other demographic and health indicators over time.
Analysed laboratory data on diarrheagenic E. coli, including DEC classification, antimicrobial susceptibility profiles, MDR definition, statistical comparisons, data reshaping, prevalence calculations, and Fisher's exact tests.
Worked with a HUCS dataset to investigate diarrhea among children under five. The analysis included variable creation, prevalence estimation, wealth-index construction using PCA, descriptive tables, and logistic regression models.
Worked with surveillance-oriented datasets and research workflows, including data cleaning, statistical analysis, reporting, visualization, and interpretation for public health research.
Designed and refined electronic data collection workflows using XLSForm and ODK, linking data collection with R-based analysis. Analytical findings were used to identify data-quality issues, improve data collection instruments, redeploy forms, and support subsequent data collection.
Technical Toolkit
My Data-to-Technology Workflow
- 1. Understand: define the research question, user requirements, variables, outcomes, and system objectives.
- 2. Design: design data structures, database schemas, collection instruments, application architecture, and user workflows.
- 3. Collect: develop structured electronic data collection instruments and digital workflows.
- 4. Build: develop frontend interfaces, backend services, APIs, databases, authentication systems, and application functionality.
- 5. Clean & Validate: identify missingness, duplicates, inconsistencies, coding issues, validation errors, and data quality problems.
- 6. Analyse: apply appropriate descriptive and inferential statistical methods.
- 7. Visualize: communicate findings through tables, figures, dashboards, reports, and interactive applications.
- 8. Improve: use user feedback, analytical findings, testing, and quality assurance to improve applications and research workflows.
- 9. Communicate: translate complex data and technical outputs into concise, decision-ready information.
What I Bring Together
My technical profile combines three complementary areas: Data Analytics, Software Development, and Public Health Research.
- Data: I transform raw and complex datasets into reliable analytical information.
- Software: I build applications, APIs, dashboards, and data-driven systems.
- Research: I understand how data is collected, managed, analysed, interpreted, and communicated in research environments.
- Public Health: I apply these technical skills to surveillance, epidemiology, laboratory research, and digital health.
This combination allows me to work across both the analytical and engineering sides of data-driven projects: from designing a data collection system and building its database, to developing the application interface, analysing the resulting data, and presenting the findings through dashboards and reports.
Contact & Portfolio
Email: aggreyongweso@gmail.com or AOngweso@kemri.go.ke
Professional Focus: Data Analytics, Software Development, Research Data Management, Statistical Analysis, Public Health Informatics, Data Visualization, Digital Health, and Health Technology.
Portfolio Interests: Public health analytics, epidemiological research, disease surveillance, geospatial data, dashboards, reproducible analysis, full-stack software development, AI applications, and digital data systems.