Vice President, Applied AI Modeling — Scale & Impact

JP Morgan Chase; New York (NY); On-site; USD 160,000 - 230,000; Full time

Benefits offered by this job

Health care coverage

On-site health centers

Retirement savings plan

Backup childcare

Tuition reimbursement

Mental health support

Financial coaching and more

Job summary

JPMorgan Chase in New York is seeking an Applied AI Modeling Lead within our Business Modeling organization to build high-impact quantitative models for our customers’ financial needs, including retail, credit card, home, auto lending, and wealth management.

You will lead modeling engagements end-to-end, mentor junior team members, and collaborate with governance to ensure robust documentation and performance tracking, using Python, TensorFlow, PyTorch, and modern data platforms.

Qualifications

• MS in a quantitative discipline (e.g., CS, Data Science, Math/Stats).
• 7+ years in Credit Cards industry modeling; 5+ years AI/ML focus.
• Proficient in Python with ML/DL frameworks; strong data libraries.
• Experience with Jupyter Notebook/Lab; ability to design analytical plans.

Responsibilities

• Develop and launch ML/AI models aligned to business goals.
• Lead end-to-end modeling engagements with stakeholders.
• Advise partners on model strengths and limitations.
• Partner with Governance for documentation and metrics.
• Coach and mentor junior team members.

Skills

Python

Analytical thinking

Communication

Modeling

Education

MS in quantitative discipline

PhD in quantitative discipline (preferred)

Tools

TensorFlow

PyTorch

NumPy

Pandas

Scikit-Learn

Jupyter Notebook

Databricks

Snowflake

Job description

JPMorgan Chase in New York is seeking an Applied AI Modeling Lead within our Business Modeling organization to build high-impact quantitative models for our customers’ financial needs, including retail, credit card, home, auto lending, and wealth management.

You will lead modeling engagements end-to-end, mentor junior team members, and collaborate with governance to ensure robust documentation and performance tracking, using Python, TensorFlow, PyTorch, and modern data platforms.