Chase Modeling - Applied AI Modeling Lead (VP)

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.

Come join us in reshaping the future!

As an Applied AI Modeling Lead, within our Business Modeling organization, you will collaborate with colleagues across JPMorgan Chase to create high-impact quantitative models for our customers’ financial needs, including retail, credit card, home, auto lending, and wealth management.

Job Responsibilities:

• Develop and launch machine learning and AI models tailored to business goals, balancing performance metrics while keeping speed to market and complexity consideration in mind.
• Lead modeling or data science engagements end-to-end, including interfacing with business, governance, and technology stakeholders, articulating clear business use cases, creating and delivering on project plans, conducting exploratory data analysis to formulate testable business hypotheses, model development and deployment, and performance monitoring.
• Be a subject matter expert and trusted advisor to business partners, helping them understand the strengths and limitations of our models.
• Partner with Governance teams to ensure comprehensive model documentation, track performance metrics, and maintain adherence to regulatory compliance standards.
• Coach and mentor junior team members, supporting their development in technical, business, and communication skills.

Required Qualifications, Capabilities, and Skills:

• M.S. degree in a quantitative discipline (e.g., Computer Science, Data Science, Mathematics/Statistics, or Operations Research).
• 7+ years of  hands-on, relevant Credit Cards industry experience in developing statistical, econometric, or machine learning (ML) models; 5+ years of hands-on experience with Artificial Intelligence (AI) such as reinforcement learning or optimization algorithms.
• Proficient in Python with hands-on experience in Machine learning and Deep learning frameworks (TensorFlow, PyTorch) and libraries (e.g., NumPy, Scikit-Learn, Pandas). Strong working knowledge of Jupyter Notebook/Lab is essential.
• Skilled at defining analytical approaches for projects by converting ambiguous business inquiries into clear, actionable analysis plans.

Preferred Qualifications, Capabilities, and Skills:

• PhD in a quantitative discipline.
• Experience developing advanced forecasting, AI, or ML models in consumer finance, financial services, tech, or a major retailer.
• AWS Certified Machine Learning or Microsoft Certified: Azure AI Fundamentals preferred. Knowledge of working on Databricks, Snowflake.