RAPHAEL MUTHEMBA

• Served as a Software Quality Analyst, focusing on the integrity and performance of critical banking software.
• Contributed to the development and testing of ananomaly detection engine for use in multiple banking institutions on KPI target achievement.
• Gained valuable experience in software quality assurance and testing methodologies, directly applicable to evaluating and ranking AI-generated code for clarity, consistency, and factual accuracy.

• Managed digital campaigns and customer inquiries, maintaining positive engagement across diverse digital platforms.
• Analyzed customer feedback to inform and support service improvement strategies, demonstrating an ability to process feedback and contribute to quality enhancement processes, relevant to providing feedback for AI model improvements.

Movie Recommendation System - MovieXplosion Platform

• Designed and implemented a sophisticated movie recommendation engine using Python, applying collaborative, content-based, and hybrid filtering techniques.
• Analyzed extensive user ratings and genre patterns to build robust predictive models, demonstrating a strong understanding of data structures and algorithms.
• Evaluated model performance rigorously using RMSE, ensuring superior accuracy and preparing models for deployment—experience directly transferable to evaluating AI-generated code for correctness and efficiency.

SyriaTel Customer Churn Prediction

• Developed and deployed advanced classification models in Python (Random Forest, Decision Tree, and Ensemble methods) to predict customer churn, showcasing strong practical application of machine learning.
• Conducted in-depth Exploratory Data Analysis (EDA) to identify key churn indicators, demonstrating meticulous attention to data integrity and pattern recognition.
• Formulated and recommended data-driven retention strategies based on model insights, highlighting the ability to translate complex data into actionable recommendations.

King County Housing Price Prediction Project

• Constructed and refined regression models in Python to accurately estimate property values for a real estate platform.
• Performed comprehensive exploratory and correlation analysis to identify critical pricing factors, applying multiple linear regression to enhance prediction accuracy and support informed pricing decisions.