Data Analytics Enthusiast
Send a job offer directly to this candidate
I am a dedicated data science enthusiast with a Bachelor of Science in Computer Science graduating in 2025 and plans to pursue a Master’s in Data Science starting this September. I have a strong foundation in linear algebra, statistics, and machine learning, complemented by hands-on experience in Python programming and SQL.
Currently, I am working on a six-month project developing a Financial Fraud Detection System. This project leverages machine learning algorithms and graph databases to identify and analyze suspicious transactions.
Neo4j, I modeled the data as a graph database, defining nodes and relationships to uncover patterns in financial activity. I implemented Isolation Forest for unsupervised anomaly detection and Random Forest for fraud classification, integrating results into a Streamlit/Flask-based dashboard to provide visualizations of fraud risk scores and relationship patterns. This project focuses on improving fraud detection accuracy while minimizing false positives, offering a scalable and user-friendly solution for financial data analysis.
