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。
Skills Required
- Master’s degree or PhD in machine learning, computer science, statistics, or a related quantitative discipline
- Experience in quantitative research, data science, or a related industry or academic field
- Strong Python programming skills
- Experience with machine learning libraries
- Familiarity with quantitative modeling, portfolio construction, and equity markets
- Experience working with large, complex, and alternative datasets
- Excellent verbal and written English communication skills
- Ability to present complex ideas to technical and non-technical audiences
- Ability to work effectively in a team environment
- Strong problem-solving skills and intellectual curiosity
- Ability to drive research projects independently
- Specialization in reinforcement learning
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Medical coverage and wellness resources, including mental-health support and wellness incentives, are described as comprehensive and accessible; feedback suggests income-based contributions help keep care affordable.
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Retirement Support — A dollar-for-dollar 401(k) match up to 5% of eligible pay, plus additional employer contributions in some cases, is highlighted as a strong pillar of financial security. Feedback suggests this structure is a notable advantage of the total rewards package.
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Parental & Family Support — Up to 16 weeks of paid parental leave for all parents, along with fertility, adoption, surrogacy, childcare, and family-support resources, signals a family-forward approach. Feedback suggests these programs are a standout feature of the package.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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