The goal of J.P. Morgan AI Research is to explore and advance cutting-edge research in AI, including ML as well as related fields like Cryptography, to develop and discover principles of impact to J.P. Morgan’s clients and businesses. J.P. Morgan AI Research has assembled a team of experts in many fields of AI. They pursue primary research in areas related to our research pillars as well as concrete problems related to financial services. Conducting AI research in financial services offers unique and exciting opportunities for impact. 

As a Research Scientist on the AI Research team, you will conduct end-to-end research typically within a specialized focus area. You will partner with internal teams to accelerate the adoption of AI within the firm. You will also work with leading academic faculty around the world on areas of mutual interest. As a member of this highly visible team, you will have the opportunity to realize significant impact not only within J.P. Morgan but also to the broader AI community.

Job responsibilities

Collaborate with internal and external researchers and applied engineering teams on multiple research projects Contribute to all aspects of the research lifecycle such as formulating problems, gathering data, generating hypotheses, developing models and algorithms, conducting experiments, synthesizing results, building prototype applications and communicating the significance of your research Produce high-impact business applications, open source software, patents and/or publications in AI/ML conferences and journals Participate in relevant top-tier academic conferences to broaden the impact of your contributions

Required qualifications, capabilities, and skills

Currently pursuing a PhD in Computer Science (especially AI/ML) or related fields  Research publications in prominent AI/ML venues; e.g., conferences, journals Strong expertise in one or more specialized areas; e.g., deep learning (DL), Reinforcement learning (RL), Explainable AI (XAI), planning, information representation and retrieval, graphs, multiagent systems (MAS), natural language processing (NLP) Practical experience with ML platforms such as Tensorflow/Keras, PyTorch, etc. Comfort with rapid prototyping and disciplined software development processes Practical software engineering experience in collaborative project settings

Preferred qualifications, capabilities, and skills

Currently pursuing a Master’s degree in Computer Science, Statistics, Engineering or related fields  Extensive programming skills in Python, Java or C++ Curiosity, creativity, resourcefulness and a collaborative spirit Clear and effective verbal and written communication skills Demonstrated ability to work on multi-disciplinary teams with diverse backgrounds Proficient understanding of fundamental AI and ML technique and practical experience with statistical data analysis and experimental design Interest in problems related to the financial services domain (specific past experience in the domain is not required)