Applied Artificial Intelligence & Machine Learning Associate

About the role

As a member of the CIB Cross-Functional Applied AI/ML team, you will have the unique opportunity to be a critical player in our firm-wide efforts to shape the future of banking. Crucial to this is helping to transform how cross-functional and operations teams operate, where you will have a direct impact on the behind-the-scenes management and functioning of the bank's corporate and investment banking services.

You will be a key member of a cross-functional team of data scientists, cross-functions and operations subject matter experts and ML engineers to design, develop and deploy scalable machine learning solutions. Our vision is to create products that transform how the firm operates, deliver measurable impact, and have the potential for commercialization.

Finance background is not a must-have. If you get as excited about machine learning theory as you get about Python development, we’d love to speak with you.

In this role, you will:

• Interact with very large datasets from different businesses in the financial domain currently not available anywhere else.
• Write production-ready code and work with tech teams to ensure your ML solution is deployable at scale across multiple lines of business.
• Develop products that can change how corporate and investment banking is done today.

Responsibilities

• Research and develop innovative ML based solutions to some of cross-functions and operations hardest problems.
• Build robust data science capabilities which can be scaled across multiple business use cases.
• Collaborate with software engineering teams to design, deploy, and maintain production-grade ML models that can be integrated with strategic systems.
• Research and analyze large data sets using a variety of statistical and machine learning techniques.
• Communicate AI capabilities and results to both technical and non-technical audiences.
• Document approaches taken, techniques used, and processes followed to comply with industry regulation.

Required Technical Qualifications and Experience

• Bachelors/Masters degree or PhD in a quantitative or computational discipline
• Considerable commercial experience in line with a capable individual contributor; developing and deploying data science and ML capabilities in production at scale.
• Strong Python development and debugging skills. Capable to develop high quality reusable code that can be leveraged from a larger group of data scientists to solve a broad spectrum of business use cases.
• Ability to work both individually and in collaboration with others, and to mentor more junior team members.
• Ability to work in agile cross-functional and operations teams and drive deliverable outcomes.
• Ability to work with non-specialists in a partnership model, conveying information clearly and creates a sense of trust with stakeholders.

Nice to Have

• Experience with deep learning frameworks (pytorch, tensorflow)
• Experience with big-data technologies (Spark, Hadoop) or distributed computation frameworks (Dask, Modin)
• Hands on experience with Natural Language Processing (NLP) and Large Language Models (LLMs)
• Experience of creating and deploying microservices
• Knowledge of MLOps concepts (CI/CD, versioning, reproducibility, observability) and development best practices

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.