Onesmus Wachira Kabui
Data Analyst | [email protected] | +254 714 049 485 | onesmus.com | linkedin.com/in/onesmuskabui
About me
Data and research-oriented Data Analyst with a strong foundation in statistical analysis, research design, and data visualization. Experienced in working with quantitative and qualitative data, transforming raw data into clear, actionable insights to support informed decision-making. Proficient in R, Excel, and SQL with a disciplined, detail-oriented approach to analysis and insight communication. On my free time, I enjoy cycling and learning German.
Work Experience
Data Engineer, Kasi Insight
*Oct 2025 - Present
- Data analysis and data visualization
- Transforming data into actionable insights that support informed decision-making
- Research design for quantitative and qualitative data collection methods
Customer Service Data Analyst, Stan Interior Designers
September 2024 - September 2025
- Apply data-driven insights to optimize customer service strategies and boost sales performance
- Analyze customer interaction data to identify trends and implement improvements
- Collaborate with sales teams to enhance customer satisfaction and revenue
Construction Worker, China Wu Yi Road Project
January 2024 - May 2024
- Contributed to road construction projects, developing strong work ethic and time management skills
- Collaborated effectively with diverse teams to meet project deadlines and quality standards
Assistant Analyst, Ndima Tea Factory
Multiple internships: Oct 2020 - Dec 2020, Oct 2022 - Dec 2022, Mar 2023 - May 2023
- Conducted field data collection on tea production, ensuring quality assurance standards
- Managed data entry for factory operations using ChaiPro (SQL-based) and observed SAP ERP transition
- Analyzed production efficiency and quality trends, presenting insights to supervisors
- Collaborated across departments to ensure accurate and timely data collection
Projects
Concrete Strength Modelling
Built regression models in R (UCI dataset) to predict concrete strength (\(R^2 = 0.63\)), identifying cement, curing age, and additives as key factors.
Obesity Level Prediction
Developed and evaluated four machine learning models (Logistic Regression, Decision Trees, Random Forest, and KNN) to predict obesity levels from lifestyle and demographic data, achieving up to \(94.5%\) accuracy.
Education
Bachelor of Science in Applied Statistics with Computing Moi University 2025
STATA Analytical Program Moi University, Completed 2019 (Distinction)
Skills
- Statistical Software: R, Python, SQL
- Data Analysis: Advanced statistical methods, predictive modeling, data visualization, research
- Microsoft Office Suite: Excel (advanced), Word, PowerPoint
- Strong communication, problem-solving, and critical thinking skills
Certifications
- STATA Analytical Program (Distinction)