AXQ Capital
Financial Services
AlgorithmicTradingResearcher
Neural analysis suggests this role is
optimal for Mid candidates.
“Algorithmic Trading Researcher at AXQ Capital. Skills: Algorithmic trading, Microstructure analysis, Trading cost analysis. Design and develop algorithms. Optimize order placement/cancellation logic”
What You'll Achieve.
Optimize trading paths; Reduce trading costs
Industry & Context.
Problem solving; Data analysis
What They're Looking For.
Must Have
Bachelor's degree or higher, 2+ years experience, Proficient in Python, Strong compiled language skills
Nice to Have
Experience with algorithm providers, Experience with HFT teams, Experience with foreign investment bank execution desks, Published research, Math/Physics/CS Olympiad awards
What You'll Do.
Design and develop algorithms
Optimize order placement/cancellation logic
Analyze market microstructure
Mine short-term prediction signals
Analyze trading costs
Evaluate strategy performance
Lead strategy iteration
Optimize backtesting system
Optimize data analysis framework
How You'll Work.
Team & Collaboration
Core trading systems
Process & Methodology
Strategy iteration
Full Job Description
关于我们 安贤投资（AXQ Capital）致力于以严谨的量化研究与先进的信息技术驱动投资。我们打造科学高效的量化研究框架，构建多市场多策略投资体系。策略布局覆盖全球股票统计套利、A股指数增强、CTA、股票日内、期货高频等领域，在全球市场部署运行，覆盖多个地区、资产类别及交易周期。自2018年成立以来，安贤持续为海内外投资者创造长期稳健的投资回报，资产管理规模稳步增长。公司在北京、上海、香港、纽约设有办公室，为国内员工提供海外交流与培训机会。 岗位职责 作为算法交易研究员（Algorithmic Trading Researcher），您将深入参与公司交易执行系统与策略的核心环节。您将专注于通过微观层面的信号和算法策略研究，优化整体资产组合的交易路径并降低交易成本。我们提供先进的高频回测基础设施与覆盖全球主要交易所的高质量数据支持。您的主要职责包括： 算法策略研发：运用概率统计、机器学习、控制理论等方法，设计、研发与优化自动化算法交易，优化报撤单逻辑 微观信号挖掘：深入分析市场微观结构、订单簿动态及其他高频L3数据，挖掘高效的短周期预测信号，用以降低交易成本 交易分析与迭代：进行全面的交易成本分析，精准跟踪、评估和分析交易算法策略的实盘表现，提出针对性改进建议并主导策略的持续迭代 系统优化与回测：参与优化高保真的算法交易模拟回测系统及数据分析框架，提升研发效率，确保回测结果与实盘执行表现的高度一致 岗位要求 国内外知名高校本科及以上学历，具有理工科（计算机、电子、数理等）或金融工程等强定量背景 具有 2 年及以上 算法交易、高频交易、做市商或相关领域的实际工作/研究经验，对市场微观结构有深入的理论认知和实践 熟练掌握 Python，并具备扎实的编译式语言开发能力，掌握或了解主流高频/大规模数据处理工具与库 对量化交易和算法交易充满热情，逻辑严谨，善于钻研，具备出色的问题解决能力和快速学习能力 加分项： 有知名算法提供商、高频交易团队、外资投行执行部门（Execution Desk）经验者优先 在顶级学术期刊或会议上发表过研究成果，或获得过国际/国内数学、物理、计算机等奥林匹克竞赛奖项
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