AMC-Quantitative Researcher -VP

Responsibility: Build clean historical datasets, and maintain point-in-time data to ensure that research uses information that was accurate and fully traceable. Run backtests and statistical checks, and study how factor performance varies across market regimes. Automate monthly signal production and suggest improvements to the process. Develop HMM, regime-switching and reinforcement learning models where appropriate. Build dashboards to keep track of data quality and strategy performance. 构建干净的历史数据集，并维护时间点数据，以确保研究使用准确且完全可追溯的信息。 运行回溯测试和统计检查，并研究因素表现如何因市场制度而异。 实现每月信号产生的自动化，并提出流程改进建议。 在适当的情况下，开发 HMM、体制转换和强化学习模型。 构建仪表板以跟踪数据质量和战略绩效。 Requirement: Master’s degree or PhD in machine learning, computer science, statistics or a related quantitative discipline. Specialization in reinforcement learning is highly desirable. Experience in quantitative research, data science, or a related field (industry or academic). Strong programming skills in Python; experience with machine learning libraries. Quantitative Modeling: Familiarity with quantitative modeling, portfolio construction, and equity markets. Data Handling: Experience working with large, complex, and alternative datasets. Excellent verbal and written communication skills in English, with the ability to present complex ideas to both technical and non-technical audiences. Collaboration: Demonstrated ability to work effectively in a team environment. Strong problem-solving skills and intellectual curiosity; ability to drive research projects independently. 硕士学位或博士学位，机器学习、计算机科学、统计学或相关定量学科专业。 具有定量研究、数据科学或相关领域（行业或学术）的工作经验。 具有优秀的技术能力，在 Python 中拥有较强的编程技能并拥有机器学习库的经验。 熟悉定量建模、投资组合构建和股票市场。 拥有处理大型、复杂和替代数据集的经验。 优秀的英文口头和书面沟通技巧，能够向技术和非技术受众提出复杂的想法。 展现出在团队环境中有效工作的能力。 强大的解决问题的技能和智力好奇心；独立推动研究项目的能力。