Chase Modeling - Applied AI Modeling Lead (VP)

JPMorgan Chase & Co.

New York (NY)

On-site

USD 150,000 - 230,000

Full time

14 days+

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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

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.
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