Quant Trading Engineer

Responsibility

• Strategy Research and Trading Execution: Participate in the design, validation, and optimization of quantitative trading strategies, including but not limited to short-term trading, arbitrage, market making, trend strategies, and risk hedging.
• Financial Product and Trading Mechanism Design: Participate in the design of trading products, trading rules, riskparameters, and market mechanisms, optimizing trading experience based on user needs and market structure.
• Market Making Strategy Support: Participate in liquidity strategy design, order book management, inventory management, risk exposure control, and other market-making related activities.
• Data Analysis and Strategy Iteration: Conduct feature analysis, signal extraction and research, strategy backtesting, and continuous optimization based on market data.
• Trading System Development: Participate in the design and development of strategy execution systems, data processing pipelines, and related trading tools, and transform them into executable trading logic.
• Live Trading Monitoring and Risk Management: Track strategy performance, analyze trading results, optimize execution efficiency, and control strategy risks.
• Engineering Implementation: Possess basic engineering capabilities and independently complete strategy module development, data processing, and API integrations.

Requirement

• 3+ years of experience in quantitative trading or quantitative research, with practical experience in digital asset markets. Candidates from funds, market-making teams, or exchanges are preferred.
• Experience in funds, quantitative teams, exchanges, market makers, or related fields is preferred.
• Deep understanding of digital asset markets, including spot trading, derivatives, order books, and liquidity mechanisms, with practical trading experience.
• Experience in financial product design or trading mechanism design, with the ability to understand and break down core rules within trading products.
• Experience with market-making strategies or liquidity management, with an understanding of key concepts such as quoting, inventory, and risk exposure.
• Strong foundation in mathematics, statistics, and probability, with the ability to conduct strategy analysis and model validation.
• Strong engineering capabilities, with the ability to use languages such as Python / Golang / C++ for strategy implementation, data processing, or trading tool development.
• Ability to independently complete data analysis, strategy backtesting, performance evaluation, and strategy iteration.