AI Researcher - Senior Associate
Headquartered in New York City, JPMorgan Chase is the largest bank in the United States.
JPMorgan's Chief Data & Analytics Office seeks an AI researcher to develop novel machine learning algorithms, models, and frameworks solving complex large-scale problems. You'll work with Python, TensorFlow/Keras, and PyTorch on commercially-oriented research projects collaborating with data scientists, engineers, and business stakeholders to create high-impact applications in financial services. The role requires a PhD in Computer Science or related field with strong ML fundamentals and research publication experience.
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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 various technical and business disciplines, contributing to high-impact business applications at the cutting edge of AI.
Job responsibilities
Work on multiple commercially-orientated research projects in collaboration with internal data scientists, applied engineering teams and business stakeholders
Formulate problems, generate hypotheses, develop new algorithms and models, conduct experiments, synthesize results, gather data, build innovative solutions, and communicate research significance
Contribute to high-impact business applications, open-source software, and patents
Develop state-of-the art machine learning models to solve real-world problems at scale
Required qualifications, capabilities, and skills
PhD in Computer Science, Engineering, or related fields
Programming skills in Python
Proficient understanding of fundamental AI and ML techniques
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, Software Engineering venues (e.g., conferences, journals)
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