Quant/ML Researcher

Senior Quant/ML Researcher for crypto/DeFi research, remote work, full research cycle from hypothesis to production.

Full cycle research on short-term microstructure, LP/hedging, execution, cross-exchange signals, risk allocation, and related crypto/DeFi tasks. Research design: hypothesis, target/labeling, baseline, metrics, causally correct OOS validation, regime analysis, and explicit GO/NO-GO criteria. Data work: source discovery, time alignment, quality control, feature engineering, and reproducible data contracts. ML/DL per problem structure; RL or other sequential control methods only when truly justified. Realistic simulation and trading economics: fees, slippage, liquidity, latency, adverse selection, impact, fill assumptions, hedging, and DEX/CEX synchronization. Paper/shadow strategies, sim-to-real analysis, and collaboration with quant developers to move proven solutions to production. Engineering standard: reproducible experiments, clean Python, critical checks, monitoring, and disciplined use of LLM/agents.

Verifiable experience in 2-3 Quant/ML projects where you personally owned a significant part of the chain from problem definition and data to validation, code, and implementation decision or GO/NO-GO. Excellent Python and strong engineering foundation: you write, debug, and review research code yourself. Strong statistics, probability, optimization, and time series work: temporal dependence, leakage, selection bias, uncertainty, and honest OOS validation. Deep practical understanding of microstructure and execution: order book/flow, liquidity, latency, fees, slippage, adverse selection, impact, sizing, and hedging. Strong practical ML/DL for sequential financial data and ability to distinguish real signal from metric optimization. High autonomy: structure unclear problems, choose the most informative experiment, quickly stop weak hypotheses, and make evidence-based decisions. Working understanding of crypto market structure. Direct DeFi/DEX experience is a plus, but strong CEX/microstructure experience can compensate with fast adaptation.

Remote work format.