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