Artificial Intelligence Research Lead

Description

The goal of JPMorgan Artificial Intelligence Research is to explore and advance cutting edge research in Artificial Intelligence, including Machine Learning as well as related fields like Cryptography, to develop and discover principles of impact to JPMorgan's clients and businesses.

JPMorgan Artificial Intelligence Research has assembled a team of experts in many fields of Artificial Intelligence and security or safety. They pursue primary research in areas related to our research pillars as well as concrete problems related to financial services. They partner with internal teams to accelerate the adoption of Artificial Intelligence within the firm. They also work with leading academic faculty around the world on areas of mutual interest. The team is headquartered in New York and present in London and the Bay Area. Conducting Artificial Intelligence research in financial services offers unique and exciting opportunities for impact. As a member of this highly visible team, you will have the opportunity to realize significant impact not only within JPMorgan Chase but also to the broader Artificial Intelligence community.

Job Responsibilities :

• As a Research Scientist in the team, you will conduct end-to-end research typically within a specialized focus area.


• You will work on multiple research projects in collaboration with internal and external researchers and with applied engineering teams.


• You will be integral 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.


• Your output will result in high-impact business applications, open source software, patents and/or publications in security/safety conferences and journals.


• As a member of the Artificial Intelligence and security/safety research community, you will also have the opportunity to participate in relevant top-tier academic conferences to broaden the impact of your contributions.

Required qualifications, capabilities and skills

• Master's degree with 7+ years or PhD with 3 + years of relevant work experience in Computer Science, Statistics, Engineering PhD in Computer Science or related fields, with a focus on security/safety


• Research publications in prominent security/safety venues, example conferences, journals.


• Expertise in one or more specialized areas of user-focused security/safety; for example: Sociotechnical aspects of Artificial Intelligence and security applications: e.g. Drivers of trust and technology adoption, assistive Artificial Intelligence. Transparent and trustworthy personalization: e.g. reputation systems for content, detecting sustained interests. Financial safety e.g. Effective warnings / education campaigns, metrics and interaction models to encourage sound financial decisions, behavioral science-based approaches. Policy/Compliance: e.g. automated techniques for supporting security compliance including drift detection and efficient reporting. Adversarial robustness, e.g. Vulnerability analysis via red teaming of our systems, adversarial Machine Learning, automated evolution of fraud protection. Authentication: e.g. Machine Learning informed challenge questions; authentication hurdles that balance usability and trust; biometrics and privacy


• Practical experience with statistical analysis tools/languages and/or ML platforms such as Tensorflow or Keras, PyTorch, etc. and software engineering experience in collaborative project settings.


• Solid understanding of the application of fundamental Artificial Intelligence and Machine Learning techniques to security/safety; e.g, Natural Language Processing based approaches to understanding security content; detecting anomalous activity

Preferred qualifications, capabilities, and skills

• 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


• Interest in problems related to the financial services domain (specific past experience in the domain is not required)