Chase Modeling - Applied AI Modeling Lead - Vice President

JPMorgan Chase & Co.; Chicago (IL); On-site; USD 150,000 - 230,000; Full time

Job summary

JPMorgan Chase & Co. is seeking an Applied AI Modeling Lead to collaborate across our Business Modeling organization. You will develop high-impact quantitative models for customer financial needs, including retail, credit cards, home, auto lending, and wealth management.

You will lead end-to-end modeling engagements, interface with stakeholders, and ensure robust model documentation and governance while mentoring junior teammates.

Qualifications

• MS degree in a quantitative field (CS/DS/Math/OR).
• 7+ years in Credit Cards industry with statistical/ML modeling.
• 5+ years AI experience including reinforcement learning or optimization.
• Proficient in Python with TensorFlow/PyTorch and libraries.
• Strong ability to translate business questions into analysis plans.

Responsibilities

• Develop and launch ML/AI models aligned to business goals balancing speed to market and complexity.
• Lead end-to-end modeling engagements with business, governance, and technology stakeholders.
• Be a subject matter expert and trusted advisor to business partners about model strengths/limits.
• Partner with Governance to ensure model documentation and compliance.
• Coach and mentor junior team members in technical and communication skills.

Skills

Python

Machine learning

Deep learning

TensorFlow

PyTorch

NumPy

Scikit-Learn

Pandas

Jupyter

Model deployment

Education

MS degree in quantitative discipline

PhD in quantitative discipline

Tools

Databricks

Snowflake

AWS

Azure

Job description

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.