VP, Applied AI Modeling Lead — Financial Services ML

JPMorgan Chase & Co.; New York (NY); On-site; USD 150,000 - 230,000; Full time

Job summary

JPMorgan Chase & Co. is seeking an Applied AI Modeling Lead to develop high-impact ML models for retail, credit card, home, auto lending, and wealth management. You will lead projects end-to-end, mentor teammates, and ensure adherence to regulatory standards.

The role requires a strong background in quantitative modeling, extensive Python ML/DL experience, and the ability to communicate complex insights to business partners. Collaboration across governance and technology teams is essential.

Qualifications

• Master of Science in a quantitative field such as CS, data science, math/ statistics or OR.
• 7+ years in Credit Cards industry with statistical/ML econometric modeling experience; 5+ years in AI (reinforcement learning or optimization).
• Proficient in Python with ML/DL frameworks (TensorFlow, PyTorch) and libraries (NumPy, pandas, scikit-learn); strong Jupyter skills.
• Ability to translate ambiguous business questions into actionable analysis plans.

Responsibilities

• Develop and launch ML/AI models aligned to business goals, balancing performance and speed.
• Lead modeling engagements end-to-end with governance, business, and tech stakeholders.
• Be a subject matter expert and advisor to business partners on model strengths and limits.
• Partner with Governance to document models, track metrics, and ensure regulatory compliance.
• Coach and mentor junior team members in technical and communication skills.

Skills

Python

TensorFlow

PyTorch

NumPy

Pandas

Scikit-Learn

Jupyter Notebook

Data analysis

Education

M.S. in quantitative discipline

PhD preferred

Tools

Databricks

Snowflake

AWS

Job description

JPMorgan Chase & Co. is seeking an Applied AI Modeling Lead to develop high-impact ML models for retail, credit card, home, auto lending, and wealth management. You will lead projects end-to-end, mentor teammates, and ensure adherence to regulatory standards.

The role requires a strong background in quantitative modeling, extensive Python ML/DL experience, and the ability to communicate complex insights to business partners. Collaboration across governance and technology teams is essential.