Web Dev and Data Analyst

1. January 2025 - August 2025

   Niebex LTD

   Developed reusable React JS components using StorybookJS

   Implemented a custom design system to ensure consistency across the application

   Created a comprehensive documentation for the design system, detailing component usage and guidelines

   Implemented central state management system using Redux Toolkit to manage application state efficiently

   Tested components using Jest and React Testing Library to ensure reliability and performance

   Collaborated with the design team to ensure the design system met the needs of the application and its users

2. April 2024 - June 2024

   Yashio Kenya

   Developed the Work Business Structure document to outline the migration process from Astro js to Next Js

   Created the Component Specification document to guide the development of website components during the migration

   Led a team of developers in the migration of numerous pages and subpages to the new framework

   Spearheaded the design phase by utilizing extensive knowledge of Next Js to create efficient components

   Implemented styling for components using CSS to enhance aesthetic appeal and functionality

   Enhanced the website's search engine optimization (SEO) by leveraging Next Js's server-side rendering capabilities

   Integrated Contentful, a content management system, to separate content from code, facilitating easier updates, deletions, and additions of data

   Utilized Redux Toolkit for central state management, improving the website's data update and addition processes

   Optimized the website architecture, reducing the number of web pages and improving navigation efficiency

3. March 2024 - April 2024

   Outreachy Internships

   Utilized Python and Jupyter Notebooks to analyze the relationship between quality scores and various feature values of Wikimedia articles

   Processed a dataset covering a two-decade span, including columns like quality_score, predicted_quality, importance_class, and more

   Explored correlations between specific quality scores (importance_class, quality_class, and pred_qual) and feature values (page_length, num_links, num_ref, num_categories, num_media, num_headings, and num_revisions)

   Created both static and interactive visualizations to clearly depict these relationships

   Fetched data on the number of page views for each article over a specified period to assess their impact on article quality scores

   Analyzed the effect of the number of revisions on the quality scores using statistical methods

   Employed technologies such as GitHub, Python, Jupyter Notebooks, Pandas, Matplotlib, NumPy, and Seaborn for data manipulation and visualization tasks

   Discovered key insights on how Wikimedia machine learning algorithms determine article quality, revealing that articles rich in wikilinks, pages, headings, references, and views tend to receive higher predicted quality scores and rank better in importance and quality classes

   Configured customizable visualizations to explore additional variables related to article quality

   Provided recommendations for further visualizations based on current research findings

1. June 2022 - November 2023

   Holberton School

   Software Engineering

2. July 2022 - October 2022

   Udacity

   Data Analysis

3. February 2018 - December 2022

   University of Nairobi

   Bachelors in Economics