PROJECTS
Here are some of my projects in Data Science and Machine Learning, showcasing my practical experience and expertise in ML models, MLOps (Machine Learning Operations), Data Analytics, Data Warehousing, Pipeline Development, Programming, Database Management, Deployment Strategies, and Report Writing. These projects highlight my ability to conceptualize, implement, and deliver robust solutions across various stages of the data lifecycle, from data acquisition and preprocessing to model training, deployment, and generating actionable insights.
Medical Data Warehouse & Data Pipeline
The Ethiopian Medical Business Data Warehouse & Analytics Platform is a comprehensive data solution tailored to enhance the efficiency and efficacy of Ethiopia's healthcare and medical sectors. This initiative is dedicated to establishing a resilient and adaptable data warehouse that integrates information from diverse stakeholders such as medical institutions, pharmaceutical firms, insurance entities, and governmental bodies. The primary goal is to provide a unified platform for comprehensive data analysis, facilitating informed decision-making and strategic advancements in the healthcare landscape of Ethiopia.
Credit Risk Modeling and Loan Optimization
This project aims to develop advanced machine learning models for credit risk assessment and loan optimization in the context of a buy-now-pay-later service. The key objectives of this project are:
Credit Scoring Model: Create a machine learning model that can accurately predict the credit risk and default probability of new customers applying for the BNPL service.
Loan Optimization Model: Develop a machine learning model that can determine the optimal loan amount, repayment period, and other terms for each applicant based on their credit profile and other relevant factors.
Insurance risk and predictive analytics
The ACIS project is dedicated to advancing risk and predictive analytics within car insurance planning and marketing in South Africa, representing an innovative insurance solution that leverages advanced technology and data analytics. The primary objectives of ACIS are to optimize insurance processes, elevate risk assessment capabilities, and enhance customer experiences, all achieved through the utilization of advanced technologies, specifically predictive modeling and data analytics.
Fraud Detection for E-commerce & Banking Transactions
The Fraud Detection project for E-commerce and Banking Transactions aims to significantly improve the identification of fraudulent activities within these sectors. It focuses on developing advanced machine learning models that analyze transaction data, employ sophisticated feature engineering techniques, and implement real-time monitoring systems to achieve high accuracy in fraud detection.
Marketing Analytics Dashboard
The Marketing Analytics Dashboard project is a comprehensive solution crafted to monitor and evaluate the effectiveness of marketing campaigns for a technologically advanced bank in Ethiopia.