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 Lead - Vice President on the AI Research team, you will conduct end-to-end research typically within a specialized focus area and collaborate on multiple research projects with internal and external researchers and applied engineering teams. Your output will result in high-impact business applications, open-source software, patents and/or publications in AI/ML conferences and journals. 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, impacting clients and businesses, with a team of experts located in New York, London, Madrid, Paris, and the Bay Area. Conducting AI research in financial services offers unique and exciting opportunities for impact to both J.P. Morgan and the broader AI community.

 

Job responsibilities

Conduct end-to-end research typically within a specialized focus area Collaborate with internal and external researchers and with applied engineering teams Engage in 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 outputs that lead to high-impact business applications, open source software, patents and/or publications in top AI/ML conferences and journals Participate in relevant top-tier academic conferences to broaden the impact of your contributions

 

Required qualifications, capabilities, and skills

PhD in Computer Science or related field with at least 2 years of experience or a MS with at least 5 years of experience in the field Research publications in prominent AI/ML venues; e.g., conferences, journals Strong expertise in one or more specialized areas of relevance e.g., LLM-based reasoning, foundational models, multimodal document analytics, knowledge representation, language processing and understanding Experience in ML platforms such as Tensorflow/Keras, PyTorch, etc. Proficiency with rapid prototyping and disciplined software development processes Expertise in software engineering within collaborative project settings

 

Preferred qualifications, capabilities, and skills

Extensive programming skills in Python, Java or C++ Interest in problems related to the financial services domain (specific past experience in the domain is not required)