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 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 with at least three years of industry experience
- 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
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