High-Frequency Quantitative Researcher (HFT Direction)

About the Company

High-Frequency Quantitative Researcher (HFT Direction)

About the Role

A short paragraph summarizing the key role responsibilities.

Responsibilities

• High-Frequency Strategy Development
• Research high-frequency trading signals and statistical arbitrage strategies for innovative financial instruments such as stocks, futures, and options, uncovering alpha from short-term market microstructures.
• Develop tick-level and order book-level predictive models, utilizing machine learning and statistical methods to enhance strategy prediction accuracy.
• Responsible for building and optimizing high-frequency backtesting frameworks to ensure the accuracy and reliability of backtest results.
• Data Analysis and Signal Mining
• Conduct in-depth analysis of massive high-frequency market data (Level2/Tick/execution logs) to extract features of market microstructure.
• Construct high-frequency factors such as order flow, volume distribution, and spread changes, evaluating their effectiveness and stability.
• Strategy Optimization and Live Implementation
• Collaborate with the C++ development team to translate strategy logic into low-latency live trading code, participating in the generation of trading signals and execution optimization.
• Monitor live strategy performance, analyze trading costs, slippage, and market impact, continuously optimizing strategy parameters and execution algorithms.
• Research and Innovation
• Track the latest high-frequency trading research from academia and industry, exploring new trading patterns and methodologies.
• Participate in team technical sharing sessions and code reviews to enhance overall research efficiency.

Qualifications

• Education and Experience
• Master's degree or higher in Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or related fields.
• At least 2 years of experience in high-frequency quantitative research, with a proven track record of profitable live strategies preferred.

Required Skills

• Solid mathematical and statistical foundation, proficient in time series analysis, stochastic processes, statistical learning, and machine learning algorithms.
• Proficient in using Python/R for data analysis, modeling, and backtesting; familiarity with C++ is a plus.
• Familiarity with high-frequency data structures (Tick, Order Book, Trade Tape) and understanding of market microstructure.
• Familiarity with Linux development environment, with strong coding practices and engineering skills.

Preferred Skills

• Experience with high-frequency strategies at top-tier quantitative hedge funds, proprietary trading firms, or market makers.
• Familiarity with FPGA, low-latency C++ development, or hardware acceleration technologies.
• Published papers in top-tier journals or conferences, or awards in mathematics/programming competitions.