Individual Member Profile

September 21, 2026

I am interested in contributing to the OpenInfra community because of its focus on open-source technologies, collaboration, innovation, and building infrastructure that enables organizations and communities to solve complex problems at scale.

With a background in Statistics and postgraduate training in Applied Statistics, I have developed strong skills in data analysis, research, problem-solving, documentation, and evidence-based decision-making. My experience working with large-scale data collection and research projects has strengthened my ability to work with diverse teams, maintain data quality, analyze information, and communicate findings clearly.
I am particularly interested in expanding my knowledge of open-source infrastructure, cloud technologies, data systems, and collaborative technology development. I see OpenInfra as an opportunity to learn from experienced professionals and contributors while also bringing my analytical, research, and problem-solving skills to community projects.

I am eager to participate actively, learn continuously, collaborate with other contributors, and contribute to projects that make open infrastructure more accessible and useful. I believe that my statistical background, curiosity, willingness to learn, and interest in technology can allow me to make a meaningful contribution to the OpenInfra community while developing my technical skills further.

Fred Mochengo is a Statistician and Data Analyst with a Bachelor of Science in Statistics and postgraduate training in Applied Statistics. He has experience in data collection, management, statistical analysis, research, fieldwork, and reporting. Fred has worked on data-driven projects involving large-scale data collection, quality assurance, research, and policy-related analysis. His experience includes working with the Kenya National Bureau of Statistics on the 2024 National School Census, as well as supporting university project evaluation and national budget reporting within the State Department for University Education. He is proficient in statistical and data-analysis tools including R, SPSS, Stata, Microsoft Excel, and other Microsoft Office applications**. His professional interests include statistical modelling, data analytics, monitoring and evaluation, research, business intelligence, and evidence-based decision-making. Fred is particularly interested in using statistical methods and data to solve practical problems, generate reliable insights, and support better decisions across research, business, government, and development sectors.