Principle Partners Limited

外资头部量化基金 买方量化研究经验优先 薪资open可谈 location: 香港/新加坡/上海/北京/悉尼/英国/美国 职位职责 开发和实施交易策略的量化模型。 进行数据分析，以识别市场低效和机会。 与其他研究人员合作，完善现有模型和策略。 回测策略，监控绩效指标并实施有效信号。 及时了解市场趋势、数据来源和技术进步。 职位要求 拥有量化领域的硕士或博士学位（例如，数学、统计、计算机科学、金融）。 在量化研究方面有证明的经验，最好是在对冲基金工作过。 精通Python、R或C++等编程语言。 对股票市场动态和股票投资组合构建有深入了解。 具备强大的分析能力，具有统计建模和机器学习技术方面的经验。 优秀的沟通能力，能够在团队合作环境中有效工作。

外资头部量化 薪资open, open to非金融/量化背景 Location: 美国/新加坡/上海/香港 • 使用深度学习模型解决公司实际问题和业务案例. • 从概念到生产实施开放式研究项目，并不断改进模型设计、工具和基础设施. • 针对量化研究和货币化过程的任何领域展开新的项目. • 参与新技术研究，及时掌握并应用深度学习的最新理论 • 计算机科学、数学（或相关学科）的博士或硕士学位 • 至少3年以上在行业和/或学术界开发深度学习系统的经验 • 有扎实的机器学习与统计基础知识，对于常用的深度学习技术 CNN, RNN, LSTM有深入的理解和实践经验 • 熟悉至少一种深度学习框架，如TensorFlow, PyTorch • Implement open-ended research projects from concept to production, continuously improving model design, tools, and infrastructure. • Launch new projects targeting any area of quantitative research and the monetization process. • Participate in research on new technologies, keeping up with and applying the latest theories in deep learning. • PhD or Master's degree in Computer Science, Mathematics (or a related field). • At least 3 years of experience in developing deep learning systems in industry and/or academia. • Solid foundation in machine learning and statistics, with in-depth understanding and practical experience of commonly used deep learning techniques such as CNN, RNN, and LSTM. • Familiarity with at least one deep learning framework, such as TensorFlow or PyTorch. • Publication at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent conferences.

外资头部基金 薪资open可谈 location: 香港/新加坡/上海/北京/悉尼/英国/美国 不限 高频 中低频 跟资产类别，机器学习经验优先 Job duties - Develop and implement quantitative models for trading strategies - Conduct data analysis to identify market inefficiencies and opportunities. - Collaborate with other researchers to refine existing models and strategies. - Backtest strategies, monitor performance metrics, and implement proven signals. - Stay updated on market trends, data sources, and technological advancements. Requirements - Master’s or PhD in a quantitative field (e.g., Mathematics, Statistics, Computer Science, Finance). - Proven experience in quantitative research, ideally within a hedge fund. - Proficiency in programming languages such as Python, R, or C++. - Strong analytical skills with experience in statistical modeling and machine learning techniques. - Excellent communication skills and the ability to work collaboratively in a team-oriented environment.