JPMorgan Chase

Compensation

Full Description

Are you passionate about quantitative research and programming? Join our US Equity Quantitative Strategy team and help shape the future of systematic equity investing. As an analyst on the US Equity Quantitative Strategy team, you will collaborate with US Equity Strategy and Global Quant Strategy teams to develop and enhance market signals, build systematic investment strategies, and support widely-followed research publications, that are often quoted in media articles. You will design scalable, testable code and reusable software components, supporting both research and client requests. This role offers the opportunity to work on innovative projects, develop new models, and contribute to the team’s global impact. Job responsibilities Develop reusable software components across all stages of our workflow, from data extraction and preprocessing to modeling, analysis, and visualization. Maintain databases, integrate new data sets, and utilize statistical and machine learning techniques to analyze market data, identify trends, and improve predictive models. Develop and monitor quantitative models and systematic strategies for equity investment. Contribute to detailed research publications and provide ongoing commentary on analyses and strategies. Stay abreast of market developments, macro events, and ML/AI innovations in systematic trading strategies through media and academic journals. Address queries from clients, work on customized client projects, and support internal partners such as Sales & Trading. Required qualifications, capabilities, and skills Strong problem-solving skills, with the ability to break down complex problems into efficient, scalable solutions and translate design into high-quality code. Demonstrated ability to write well-structured, maintainable code following best practices for readability and reusability. Strong programming skills in Python (especially time-series handling) are essential. Proficiency in statistical analysis and machine learning / AI techniques. Education in Computer Science, Software Engineering, Quantitative Finance, Mathematics, Statistics, Data Science/AI, Engineering, or a related field. Basic knowledge of financial platforms such as Bloomberg, Factset, or Capital IQ. Strong communication skills, with the ability to convey complex concepts to non-technical stakeholders. Ability to work effectively in a team environment, communicate clearly, and contribute to collaborative coding efforts. Preferred qualifications, capabilities, and skills Experience developing systematic investment strategies for equities. Familiarity with additional programming languages (e.g., R, SQL, C++) and cloud technologies. Ability to create powerful visualizations and communicate insights effectively. Experience supporting research publications and client requests in a fast-paced environment.