I'm an AI/ML engineer focused on building intelligent, data-driven systems that solve real-world problems at the intersection of machine learning and quantitative finance. My work spans the full spectrum — from exploratory research and model development to production-grade deployment.
My core expertise includes Machine Learning, Deep Learning, Quantitative Finance, Predictive Analytics, Time Series Forecasting, and Algorithmic Trading. I design and implement end-to-end AI pipelines that take ideas from research notebooks to live, production-ready systems.
I'm passionate about applying advanced ML techniques — signal processing, ensemble methods, Monte Carlo simulation, and multi-factor modeling — to extract actionable intelligence from complex, noisy financial data.
An intelligent trading analysis and execution platform that leverages 400+ ML-driven strategies with real-time signal generation, automated trade execution, and adaptive risk management across Forex, Crypto, and Indices markets.
Key Highlights: Dual-server architecture · Real-time technical analysis · Automated position management · Confidence scoring engine · Multi-timeframe signal fusion · Risk-controlled execution with drawdown enforcement
A multi-phase quantitative research engine that systematically discovers, validates, and optimizes trading strategies using bar-by-bar simulation, Monte Carlo stress testing, and ensemble combination search across 50+ technical indicators.
Key Highlights: 14-phase research pipeline · 400+ strategy evaluation · Train/validation/test data splits · Parameter & exit optimization · Monte Carlo risk simulation · Out-of-sample validation · Production-ready config generation
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