Crypto high-frequency market-making arbitrage

Utilizing statistical modeling, machine learning, and time series analysis, etc., to study market microstructure, build a high-frequency trading signal model, and form high-frequency predictive ability.

Perform attribution analysis on high-frequency strategy performance, identify sources of returns and risk factors.

Requirements:

At least 1 year of trackable performance, Sharpe Ratio 5-10;

2 years of WEB3 quantification experience,

Master's degree or above from well-known domestic and foreign universities, majoring in mathematics, physics, statistics, financial engineering, etc., are preferred;

Familiar with the development process and methodology of quantitative strategies, those with well-known quantitative institutions are preferred;

Proficient in using Python, C++, Java, etc. to process massive financial data;

Have good team spirit and communication skills, strong sense of responsibility and stress resistance ability

Remote work, base Hong Kong, Singapore, New York, etc.