About the Role

This role focuses on discovering sustainable predictive signals within the global digital asset markets while deeply engaging in the design of live execution and risk management logic. Distinguishing itself from purely theoretical research, this position emphasizes a physical intuition for Market Microstructure and the continuous optimization of Execution Alphas. As a core team member, you will operate in a high-logic-density environment, transforming massive unstructured datasets into profitable live trading strategies.

Responsibilities

Alpha Design & Validation: Design and validate systematic alpha factors across price, order book, funding, flow, and microstructure data.
Pipeline Ownership: Build and own an end-to-end alpha research pipeline (data → feature → signal → evaluation).
Factor Analysis: Run rigorous factor analysis (IC, IR, decay, regime sensitivity, turnover, etc.).
Iteration & AI Exploration: Iterate and improve alpha signals rapidly, and explore AI-assisted research workflows to maximize development efficiency.
Risk Management & Dynamic Hedging: Responsible for the real-time measurement of strategy risk exposures (Greeks/Net Exposure) and designing dynamic hedging schemes to ensure system robustness during extreme market volatility.
P&L Attribution & Iteration: Conduct in-depth P&L Attribution for live strategies, accurately identifying causes of signal decay or execution slippage to facilitate rapid model recalibration.

Qualifications

3+ years of experience in quantitative strategy research or live trading. Backgrounds in Digital Assets (Crypto), Hedge Funds, or Proprietary Trading firms (Prop Shops) are highly preferred.
Proven track record in Full-Lifecycle quantitative trading (encompassing factor mining, backtesting evaluation, engineering implementation, and live P&L attribution).
Strong grasp of Mathematics/Statistics. Proficient in time-series analysis and cross-sectional regression, with a rigorous approach to combating Overfitting and Data Leakage/Look-ahead bias.
A "Hands-on" Python expert (Pandas, NumPy, Scikit-learn), capable of writing high-performance, vectorized research code.
AI Workflow experience utilizing the AI toolchains (e.g. Cursor, LLM based coding) and "Vibe Coding" patterns to dramatically accelerate R&D velocity is a significant plus.
Exceptional logical decomposition skills. You have a relentless drive for rapid iteration and thrive when solving complex, hardcore problems in a fast-paced, flat-structured, and high-density environment.

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