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🚀 About Me

I work at the intersection of quantitative finance and machine learning, building signal-driven research systems and production-grade ML/AI pipelines.

• 🔭 Focused on alpha research, signal engineering, and ML/LLM systems
• 🧠 Interested in market microstructure and evaluation metrics
• 🧰 Build end-to-end pipelines (data → research → backtest → deploy/monitor)
• 💬 Python, backtesting, ML systems, RAG/LLMs, MLOps, Docker/K8s

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📊 Quant Finance (What desks care about)

• Alpha research: short-horizon, market & sector neutral
• Signal classes: momentum, reversal, liquidity, volatility
• Evaluation: Sharpe, IC, turnover, drawdown, fitness
• Microstructure: OFI, Kyle’s Lambda, liquidity impact
• Platforms: WorldQuant BRAIN, custom Python backtests

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🤖 Machine Learning & AI Systems

• End-to-end ML pipelines (training → inference → monitoring)
• LLM systems: RAG, agents, evaluation
• Model versioning, rollback, latency & cost awareness
• Cloud-native, container-first systems

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🛠️ Technical Stack

Core

Quant / Data

ML / Deep Learning

LLMs / GenAI

Infra / MLOps

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📈 GitHub Stats

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📈 Activity Graph

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🌐 Connect With Me

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💡 “Chasing signal. Building systems.”