Aspiring Cyber Fraud Analyst with a passion for digital forensics and data anomaly detection. I leverage Python, SQL, and statistical analysis to uncover financial risks.
When I'm not analyzing data, you can find me 🍳 Cooking new recipes, 📸 Photographing streets, or ✈️ Travelling to new places.
A Python-based machine learning pipeline utilizing Scikit-Learn to detect fraudulent transactions in imbalanced datasets with 90%+ accuracy.
Advanced SQL logic engine to flag "Velocity Attacks" (rapid transactions) and "Whale Anomalies" (high value) using Window Functions.
A cybersecurity desktop application built with Tkinter to securely hide encrypted messages within digital images using LSB encoding.
I am currently available for immediate joining in Delhi/NCR.
Feel free to reach out if you have an open position or just want to discuss fraud analytics.