Quantitative Researcher — High Frequency Equities (US Markets, New York) Location: New York, HK, China Responsibilities • Analyze diverse datasets across US equity and futures markets to identify quantifiable trading edges and discover actionable alpha signals in high‑ and mid‑frequency domains. • Conduct end‑to‑end research including alpha factor mining, feature engineering, model construction, backtesting, and strategy optimization with realistic transaction cost and execution modeling. • Design and run robust backtests, walk‑forward validation, and stress tests to ensure signal stability and economic significance. • Collaborate with execution, engineering, and risk teams to translate research into production‑ready strategies and support live deployment/monitoring. • Execute critical research initiatives that directly support trading decision‑making and performance attribution. Requirements • Bachelor's, Master's, or PhD in Statistics, Physics, Computer Science, Mathematics, or another quantitative field. • Proven hands‑on experience with high‑frequency US equity trading (experience with tick‑level data, microstructure, order book dynamics, and execution constraints is required). • Proficiency in at least one programming language: Python (preferred), C++, C#, MATLAB, or R. • Strong data engineering and numerical skills for handling large tick‑level datasets and building scalable backtesting pipelines. • Ability to read and synthesize academic/technical English literature and rapidly learn new technical domains. • Intellectual curiosity, rigorous analytical thinking, and structured problem‑solving skills; strong attention to model validation and risk controls. Preferred • Competition awards (e.g., IMO/IPhO/ACM‑ICPC) or strong contest performance. • Publications in top‑tier peer‑reviewed journals or conferences. • Experience with low‑latency systems, co‑location, market data feeds, and execution optimization techniques. • Familiarity with cloud/container technologies and production deployment (Docker, CI/CD, etc.). How to apply • Please submit your CV and a brief summary of relevant HF experience, including the markets/data you worked with, example signals or strategies developed, and any performance/production outcomes.