The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.

As an AI Research Senior Associate in J.P. Morgan AI Research, you will work on novel techniques, tools, and frameworks to model and solve complex large-scale problems, collaborating with experts in AI Agents and contributing to high-impact business applications and the broader AI community. Your role involves formulating problems, generating hypotheses, developing algorithms and models, conducting experiments, and communicating research significance. Your output will result in publications, high-impact business applications, open-source software, and patents.

Job responsibilities

Work on multiple research projects in collaboration with internal and external researchers and applied engineering teams

Formulate problems, generate hypotheses, develop new algorithms and models, conduct experiments, synthesize results, gather data, build prototypes, and communicate research significance

Contribute to publications in AI/ML conferences and journals, high-impact business applications, open-source software, and patents

Participate in relevant top-tier academic conferences, organize workshops, and engage with the AI research community to broaden the impact of your contributions

Required qualifications, capabilities, and skills

PhD in Computer Science, Statistics, Engineering, or related fields

Programming skills in Python

Proficient understanding of fundamental AI and ML techniques (e.g., A*, regularization)

Practical experience with statistical data analysis and experimental design

Curiosity, creativity, resourcefulness, and a collaborative spirit

Effective verbal and written communication skills with technical and business audiences

Demonstrated ability to work on multi-disciplinary teams with diverse backgrounds

Interest in problems related to the financial services domain

Preferred qualifications, capabilities, and skills

Research publications in prominent AI/ML or Software Engineering venues (e.g., conferences, journals)

Strong expertise in specialized areas such as deep learning (DL) or AI Agents

Practical experience with ML platforms such as TensorFlow/Keras, PyTorch

Comfort with rapid prototyping and disciplined software development processes

Practical software engineering experience in collaborative project settings

Hands-on experience developing and using AI Agents in a professional setting