With over 4 years of experience in developing end-to-end predictive machine learning solutions, I specialize in transforming complex datasets into actionable business strategies. My expertise encompasses Customer Analytics, Churn Prediction, and AI-Driven Insights, empowering organizations to drive growth and maximize value through data.
I am a Data Scientist with 4+ years of experience developing predictive and prescriptive machine learning solutions across mobile money, telecom, and research environments.
My expertise lies in building robust models for customer segmentation, churn prediction, and revenue forecasting. I have hands-on experience deploying deep learning models into production and translating complex business challenges into actionable AI-driven insights.
Currently, I work as a Pricing & CVM Analyst at Mixx by Yas, where I leverage data to optimize pricing strategies and enhance customer value.
4+ Years
Machine Learning
Dar es Salaam
Developed robust classification models (Logistic Regression, Random Forest, XGBoost) to predict customer churn using behavioral and transaction data. Performed comprehensive EDA and feature engineering to identify key churn drivers.
Built advanced time-series forecasting models using ARIMA and Prophet to predict transaction volumes and revenue trends. The system supports strategic business planning and pricing decisions with high-accuracy forecasts.
Implemented Unsupervised Learning models (K-Means, Hierarchical Clustering) using transaction frequency and monetary value metrics. Successfully identified high-value, growth, and at-risk customer segments for targeted marketing strategies.
Built a Natural Language Processing pipeline using BERT to analyze customer feedback from social media and support tickets. Automated the categorization of customer issues and sentiment tracking to identify service pain points in real-time.