Quantitative Trading Simulator
Developed an algorithmic trading simulator in Python using Pandas & NumPy to backtest multi asset strategies on historical data.
Computer Science student specializing in software engineering, data analytics, and cybersecurity.
Designed and deployed AI-powered communication tools. Built & fine-tuned machine learning models for chatbot intelligence and analytics, improving interaction by 40%. Designed cloud native microservices and MLOps workflows using Azure + AWS.
Engineered automated Python + SQL data pipelines to collect, clean, validate 50K+ production records. Applied statistical & regression modelling to identify production inefficiencies, improving yield by 22%.
Developed and launched a Flutter-based mobile platform with Firebase integration. Optimized code architecture decreasing average load times 35% while supporting 10K+ active users.
Developed an algorithmic trading simulator in Python using Pandas & NumPy to backtest multi asset strategies on historical data.
Built an NLP model using BERT to analyze market headlines and classify sentiment polarity. Achieved over 90% sentiment classification accuracy.
Designed event driven workflows using AWS Lambda and Python to automate recurring ETL and reporting processes. Reduced manual workload by 70%.
Built a responsive dashboard with React and WebSocket for live data streaming. Achieved sub second update latency for real time insights.
Developed an end to end ML pipeline in Python to predict credit and operational risk scores. Enhanced data reliability by 25%.
Always interested in new opportunities, collaborations, and conversations about technology and design.