About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 439 open roles on FindRole.

Listed pay typically runs $152,000–$215,000 across 233 roles with salary data.

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At a glance

TL;DR · AI Modeling Lead, Connected Commerce and Cards

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As an AI Modeling Lead in the Connected Commerce and Cards team at JPMorgan Chase, you will design, train, and deploy machine learning models to address complex business challenges in consumer finance. Your day-to-day responsibilities include leading end-to-end modeling projects, collaborating with stakeholders across governance and technology teams, ensuring model documentation adheres to regulatory standards, and mentoring junior data scientists. You will work extensively with Python, TensorFlow, PyTorch, and other modern AI tools while contributing to the broader AI/ML community through research or open-source projects. This role requires a deep understanding of consumer finance and experience in developing advanced models for financial services, ensuring that your work is both innovative and compliant with regulatory requirements.

Skills

Python TensorFlow PyTorch NumPy Scikit-Learn Pandas Jupyter Notebook Databricks Snowflake Git CI/CD LLMs Generative AI Reinforcement Learning Optimization Algorithms

What you'll do

Design and deploy machine learning models tailored to business goals in commerce use cases.
Lead end-to-end modeling engagements, including stakeholder interfacing and model deployment.
Ensure comprehensive documentation and adherence to regulatory compliance standards for models.
Coach junior team members in technical skills and set a culture of hands-on coding.
Develop advanced AI or ML models with a focus on consumer finance and financial services.

What we're looking for

M.S. degree in a quantitative discipline (e.g., Machine Learning/AI, Computer Science).
5–7 years of hands-on experience developing machine learning models.
Proficiency in Python and deep learning frameworks like TensorFlow and PyTorch.
Experience with Databricks and Snowflake for data processing and analytics.
Strong understanding of AI tooling and practical judgment in selecting tools.
Track record of shipping advanced AI/ML models in consumer finance or tech.
Knowledge of modern engineering workflows including version control and testing.