Profile Details Beta
Summary
Self-taught quantitative developer focused on building production-style crypto trading systems. Designed and implemented a Top-Movers microstructure scanner and GMGN signal engine analyzing 200+ crypto futures symbols in real time. Experienced in order-flow imbalance (OFI), liquidity analysis, sweep/reclaim detection, and regime filtering to generate high-confidence trading signals.Built modular Python research pipelines for signal generation, backtesting, and evaluation using reproducible simulated market data. Backtested multiple mock strategies across 500k+ simulated trades, achieving ~65% directional signal correctness over short test windows. Strong focus on system design, robustness, and metric-driven iteration rather than curve-fitting.
Comfortable working end-to-end: data ingestion, signal logic, validation, logging, and offline analysis. Actively seeking roles where I can contribute to crypto trading infrastructure, quantitative research systems, or execution pipelines in a fast-moving environment.
Experiences
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In Crypto Since
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