📊 Customer Segmentation & Churn Analysis project completed as part of a Business Analyst Internship at Saiket Systems.

Enterprise-grade Telecom Customer Churn Prediction system blending advanced machine learning (XGBoost), real-time Flask API deployment, and interactive Streamlit dashboards to enable data-driven customer retention strategies.

📡 Multimodal AI system for Telecom Customer Churn Prediction using ML, DL + Sentiment Analysis. Includes Business Dashboard, SHAP Explainability, PDF Reports & Batch Processing.

End-to-end telecom customer churn analysis using Python, matplotlib, seaborn, NumPy and statistics to identify churn drivers and support retention decisions.

This project uses real-world telecom customer data to predict churn behavior using machine learning. It includes data cleaning, exploratory data analysis (EDA), feature engineering, model training (Logistic Regression and Random Forest), and strategic business recommendations. The final model is ready for deployment in customer retention systems.

Analyzing telecom customer churn using Python, SQL, and Power BI. Interactive dashboard and charts showcase insights to reduce churn.

this project focuses on predicting telecom customer churn using supervised machine learning models. by analyzing historical data such as contract type, internet service usage, and billing method, we aim to identify customers who are at risk of leaving the company.

Strategic Intelligence Agent (SIA) is an autonomous multi-agent framework powered by LangGraph and Llama-3.3-70B. It proactively identifies at-risk telecom subscribers and deploys hyper-personalized retention protocols to mitigate churn and protect recurring revenue.

Customer churn prediction system using XGBoost, SHAP explainability, and Streamlit for real-time telecom retention analysis.

Random Forest Classifier for Customer Churn Prediction

This project leverages Python (Pandas, Prophet, Matplotlib) to track segment-wise performance, calculate kebele-level market penetration rates, and deliver a 12-month forecast. Provides actionable geographic and segment-specific insights for resource allocation and and strategic planning.

A full data analytics case study that identifies why telecom customers churn, predicts future churn with machine learning, and visualizes actionable business insights in Power BI dashboards.

Power BI dashboard analyzing the business impact of the 5G launch on Wavecon Telecom by comparing revenue, ARPU, customer metrics, market share, and plan performance before and after 5G.

📈 Analyze subscriber growth and market opportunities for telecom services in Wolaita Sodo, Ethiopia, using data-driven insights and forecasts.