Prop mm quant trader

My client is a market-making firm.

English

About the Role

We are looking for a Quantitative Market Making Trader to take responsibility for the live operation, data analysis, and optimization of market-making strategies across digital asset spot and derivatives markets.

This role combines live strategy execution and monitoring with quantitative research . You will be directly involved in the continuous development and iteration of high-frequency market-making strategies, using data-driven analysis to improve trading logic, strategy profitability, and overall market competitiveness.

Responsibilities

1. Live Strategy Operation

• Operate and monitor high-frequency market-making strategies on a daily basis, continuously tracking strategy performance and risk metrics to ensure stable and reliable production trading.
• Quickly identify and resolve trading issues, including market data anomalies, order issues, execution anomalies, and risk-control events.
• Continuously monitor live strategy performance, analyze changes in trading results, and drive improvements and issue resolution.
• Work closely with the engineering team to deploy new strategies, iterate existing versions, and continuously improve the trading system.

1. Strategy Research and Optimization

• Analyze order book, trade, and order flow data to continuously improve market-making strategies.
• Study market microstructure and optimize quote placement, order cancellation logic, inventory management, and risk controls.
• Use both historical and live trading data to continuously improve key strategy metrics, including PnL and quote lifetime.
• Adjust strategy parameters according to different market conditions to reduce losses caused by adverse selection.
• Continuously research new trading signals, execution logic, and strategy improvements to enhance the overall competitiveness of market-making strategies.

Requirements

Basic Qualifications

• Bachelor's degree or above in Computer Science, Mathematics, Statistics, Financial Engineering, or a related field.
• Strong understanding of digital asset spot and derivatives markets and their trading mechanisms.
• Strong understanding of order books, matching engines, and market microstructure.
• Proficiency in Python for data analysis, strategy validation, and development of analytical and automation tools.
• Familiarity with Linux, SQL, Git, and related development tools.
• Strong data analysis skills, with the ability to identify issues from trading data and develop practical, actionable solutions.
• Strong analytical and logical thinking, with a continuous improvement mindset.

Preferred Qualifications

Candidates with any of the following experience or skills will be preferred:

• Experience in digital asset market making, high-frequency trading, quantitative trading, or exchange-based quantitative trading teams.
• Proficiency in C++.
• Experience with event-driven trading systems and low-latency trading architectures.
• Research or practical experience in any of the following areas:
• Inventory management for market-making strategies
• Fill probability modeling
• Toxic order flow analysis
• Market microstructure research

What We Look For

• Ability to independently analyze changes in strategy performance and identify the underlying causes of PnL deterioration.
• Ability to continuously optimize quoting logic, order cancellation logic, and inventory management through data-driven analysis.
• Ability to identify issues in live trading, propose improvements, and drive them through to implementation.
• Strong interest in high-frequency trading, market microstructure, and quantitative market making, with a willingness to continuously learn and conduct research.
• Strong sense of ownership and responsibility, with the ability to respond quickly to and resolve issues in a production trading environment.

If you are interested in continuously improving high-frequency market-making strategies rather than simply maintaining them, and if you enjoy using data to improve trading performance and working closely with strong engineering and trading teams to build competitive market-making strategies, we would love to hear from you.

中文

量化做市交易员（HFT）

岗位介绍

我们正在招聘量化做市交易员，负责数字资产现货及衍生品做市策略的线上运行、数据分析及策略优化。

这是一个兼具 线上策略运行 与 策略研究 的岗位。你将直接参与高频做市策略的持续迭代，通过数据分析不断优化交易逻辑，提升策略收益和市场竞争力。

岗位职责

一、线上策略运行

• 负责高频做市策略的日常运行，持续监控策略表现及风险指标，保障策略稳定运行。
• 快速定位并处理交易异常，包括行情异常、订单异常、成交异常及风控事件。
• 持续跟踪策略运行情况，分析策略表现变化，并推动问题解决及优化。
• 与研发团队协作，推动策略上线、版本迭代及交易系统持续优化。

二、策略研究与优化

• 基于订单簿、成交数据及订单流开展数据分析，持续优化做市策略。
• 研究市场微观结构，优化挂单位置、撤单逻辑、库存管理及风险控制。
• 通过历史数据及线上交易数据，不断提升策略盈亏和挂单时间等核心指标。
• 根据不同市场状态调整策略参数，降低逆向选择带来的损失。
• 持续研究新的交易信号、执行逻辑及策略优化方向，提高做市策略整体竞争力。

任职要求

必备条件

• 本科及以上学历，计算机、数学、统计、金融工程等相关专业。
• 熟悉数字资产现货及衍生品交易机制。
• 熟悉订单簿、撮合机制及市场微观结构。
• 熟练使用 Python 进行数据分析、策略验证及自动化工具开发。
• 熟悉 Linux 开发环境及 SQL，Git等工具。
• 具备较强的数据分析能力，能够通过交易数据发现问题，并提出可落地的优化方案。
• 具备良好的逻辑分析能力及持续优化意识。

优先考虑

满足以下任一条件者优先：

• 有数字资产做市、高频交易、量化私募或交易所量化团队工作经验。
• 熟悉 C++。
• 熟悉事件驱动交易系统及低延迟交易架构。
• 具备以下任一方向的研究或实践经验：
• 做市策略库存管理
• 成交概率建模
• 订单毒流分析
• 市场微观结构研究

我们希望你具备以下能力

• 能够独立分析策略表现变化，并定位收益下降的原因。
• 能够通过数据分析持续优化挂单逻辑、撤单逻辑及库存管理。
• 能够针对线上交易过程中发现的问题提出改进方案，并推动优化落地。
• 对高频交易、市场微观结构及量化做市有浓厚兴趣，并愿意持续研究和学习。
• 具备较强的责任心，能够在生产环境中快速响应和解决问题。

如果你希望参与高频做市策略的持续优化，而不仅仅是策略维护；如果你愿意通过数据分析不断提升交易表现，并与优秀的研发及交易团队共同打造具有竞争力的做市策略，我们期待你的加入。