Location: New York, NY, United States

Job Summary

As a part of the team of portfolio managers, data scientists, and ML Engineers, you will design, build, and operationalize AI/ML capabilities that contribute directly to the team’s investment process—from research through production.  Your problem-solving capabilities will have a high impact on the team’s efforts to identify investment opportunities for the US Equity portfolios managed by the team. 

 

Job Responsibilities 

• Implement scalable data ingestion and transformation pipelines for financial and alternative data
• Design, deploy, and operate inference services and monitoring for large models
• Contribute to robust workflows: experiment tracking, reproducibility, evaluation, and post-deployment monitoring
• Work closely with the portfolio management team to develop new investment capabilities
• Optimize cost, performance, and reliability in cloud environments

Required Qualifications, Capabilities, and Skills:

• 3+ years of relevant experience building large-scale data and modeling pipelines
• Strong proficiency in Python and experience working with REST APIs and OAuth workflows
• Advanced familiarity with cloud computing platforms (e.g., AWS, Google Cloud, Azure)
• Intellectual curiosity and passion for problem solving

Preferred Qualifications, Capabilities, and Skills:

• Experience working with large-scale natural language processing workflows
• Strong familiarity with deep learning frameworks and libraries (e.g. PyTorch, Tensorflow)
• Demonstrated success deploying systems into cloud environments (AWS preferred)
• Interest in financial markets and Equity market investing

 

Fundamental Data Science (FDS) is an investment capability within the U.S. Core Equity group at J.P. Morgan Asset Management. The FDS t