6+ Years Experience · API & ETL Systems · Published Author · Technical Trainer
I design production-grade APIs and data systems, teach others to do the same, and published a comprehensive book on building production data science pipelines with R. From RESTful API architecture to ETL orchestration and multi-step approval workflows, I build structured, observable systems that handle complex real-world interactions.
I do not just analyze data — I build systems that make data reliable, scalable, and actionable.
I am Musa Rioba, a Data Engineer with a BSc in Actuarial Science from Karatina University and 6+ years of hands-on experience designing production APIs, ETL pipelines, and multi-step workflow systems across freelancing, technical training, and open source.
I wrote "Production Data Science with R" — a comprehensive guide covering
end-to-end ML pipelines, automated ETL with targets, real-time fraud detection
with Redis, interactive dashboards with Shiny, and robust A/B testing frameworks.
Every chapter follows production best practices: reproducibility, scalability, observability, and safety.
My background in actuarial science and technical training has honed my ability to break down
complex tasks into precise, logical steps — a skill I apply to API design and structured system interactions.
Beyond the book, I have published three open-source R packages (ugcensus, sacensus, kenyacensus), built production APIs and dashboards with role-based access control, and spent 4 years as a Technical Trainer teaching data analysis, API design, and programming to over 100 students and professionals.
"Production Data Science with R" — 8 chapters on production-grade data systems
RESTful API design, ETL orchestration, multi-step workflows, ML pipelines, and automated systems
4 years teaching data analysis, R, Python, and production best practices
3 published R packages, live dashboards, production APIs, and production-tested tools
A hands-on guide for data scientists who want to move beyond notebooks and build systems that run in production.
Production-ready tools and packages that handle the full data pipeline from raw sources to interactive outputs.
A full-stack usage-based insurance (UBI) platform for the Kenyan motor insurance market. Features a Flutter mobile app and a production REST API backend with 10+ structured endpoints handling authentication, scoring, driver profiles, and audit trails — designed for reliable request/response patterns and stateful multi-step interactions.
A production-grade ETL/ELT data platform that ingests raw sales, customer, and product data from multiple sources, cleans and transforms it, and delivers analytics-ready datasets for business reporting. Designed to run on a standard 16GB RAM laptop.
A production-ready Phase II diabetes clinical trial monitoring system using CDISC SDTM data. Features a multi-step role-based access workflow (Investigator → Monitor → Admin) with state transitions, audit logging, and safety tracking — deployed via Docker and Shinyapps.io with GitHub Actions CI/CD.
A production-ready business intelligence dashboard for sales analytics and executive reporting. Features reactive filters, KPI cards with trend indicators, interactive Plotly charts, sortable data tables, and one-click CSV export — all in a responsive dark theme.
A comprehensive insurance marketplace platform for Kenya's insurance market. Features 4 premium calculators, company directory, market analysis, regulatory compliance tracking, and NHIF benefits — all in one interactive dashboard.
A comprehensive toolkit for accessing, analyzing, and visualizing Uganda census data from the Uganda Bureau of Statistics (UBOS). Supports 1991, 2002, 2014, and 2024 censuses.
A comprehensive toolkit for accessing, analyzing, and visualizing South African census data from Statistics South Africa (Stats SA). Supports 1996, 2001, 2011, and 2022 censuses.
A comprehensive toolkit for accessing Kenya's Population and Housing Census data from the Kenya National Bureau of Statistics (KNBS). Covers 1948 to 2019 with 13 themed datasets.
Deep expertise in R-based production systems, with expanding skills in SQL, cloud, and orchestration.
Download my updated resume in PDF or Word format. Print-ready and professionally formatted.
Times New Roman, 12pt. Clean single-column layout. Includes all projects, skills, and experience.
I am open to opportunities where I can apply my expertise in API design, structured data systems, multi-step workflow logic, and precise technical communication to build high-quality, production-grade solutions.