Quant Strategy Pipeline Development: Build and refine the end-to-end quantitative trading strategy pipeline — from data ingestion, factor computation, model prediction, backtesting through to live execution — improving research efficiency, deployability, and reproducibility.
Trading System Integration: Collaborate with engineering and data teams to solve technical challenges including data connectivity, low-latency execution, and strategy deployment, ensuring stable strategy operation in production.
Cross-Market AI Trading: Explore the adaptation and implementation of AI-driven trading across both traditional financial markets (equities, futures) and on-chain asset markets, leveraging the unique characteristics of each.
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