Applied AI Modeling Lead — Finance & ML Innovator

Testing Site - JPMC; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase in New York, NY seeks an Applied AI Modeling Lead to collaborate across the organization and develop high-impact ML models for retail, credit, and wealth management. You will drive end-to-end modeling initiatives, balancing performance with regulatory requirements and business needs.

The role requires leadership in model development, deployment, and stakeholder communication, plus mentoring junior team members in a fast-paced, data-driven environment.

Qualifications

• M.S. degree in a quantitative discipline.
• 7+ years of hands-on experience in the Credit Cards industry developing statistical, econometric, or ML models.
• 5+ years of hands-on AI experience such as reinforcement learning or optimization algorithms.
• Proficient in Python with hands-on experience in ML/DL frameworks (TensorFlow, PyTorch) and libraries (NumPy, Scikit-Learn, Pandas).

Responsibilities

• Develop and launch ML/AI models tailored to business goals, balancing performance with speed to market.
• Lead modeling/data science engagements end-to-end with business, governance, and tech stakeholders.
• Be a subject matter expert to help partners understand model strengths and limitations.
• Partner with Governance to ensure model documentation, performance tracking, and regulatory compliance.
• Coach and mentor junior team members in technical, business, and communication skills.

Skills

Credit Cards experience

AI/ML experience

Analytical thinking

Stakeholder communication

Education

M.S. in quantitative discipline

PhD in quantitative discipline (preferred)

Tools

Python

TensorFlow

PyTorch

NumPy

Pandas

Scikit-Learn

Jupyter Notebook

Job description

JPMorgan Chase in New York, NY seeks an Applied AI Modeling Lead to collaborate across the organization and develop high-impact ML models for retail, credit, and wealth management. You will drive end-to-end modeling initiatives, balancing performance with regulatory requirements and business needs.

The role requires leadership in model development, deployment, and stakeholder communication, plus mentoring junior team members in a fast-paced, data-driven environment.