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Job Description

Come join us in reshaping the future of banking with AI!

As an Applied AI Modeling Executive Director, within our AI Modeling Data and Analytics organization, you will architect the development of next-generation AI ML solutions that power JPMorgan Chase’s business decisions, with a focus on credit card and lead a team of experts in designing, deploying, and scaling robust AI/ML systems, leveraging state-of-the-art architectures, as well as deep learning and advanced modeling techniques to solve complex business challenges.

Job Responsibilities:

  • Design and oversee the integration of advanced machine learning and deep learning architectures and agents. Into production environments in partnership with Product, Risk, Finance, Operations, Technology, and Compliance
  • Partner with the Business Stakeholders and break down silos to translate business needs into technical solutions while managing the full AI/ML lifecycle
  • Lead emerging AI talent in research and adoption of cutting-edge AI techniques, including deep neural networks, reinforcement learning, causal inference, and foundational models, to address high-impact business problems
  • Establish best practices for model development, MLOps, and cloud-native deployment, ensuring compliance with governance and regulatory expectations and promoting skill mastery and continuous learning on the team
  • Build and lead a high-performing team of AI/ML scientists and engineers and provide individualized development plans, structured rotations, and visibility to senior stakeholders
  • Oversee rigorous validation, documentation, and monitoring of models, proactively identifying risks and ensuring adherence to internal and external standards while coaching the team to carry these standards into future leadership roles

Required Qualifications, Capabilities, and Skills:

  • Advanced degree (PhD or MS) in Computer Science, Machine Learning, Mathematics, Statistics, Engineering, Economics or other related fields
  • 10+ years of hands-on experience in designing, developing, and deploying advanced AI/ML models, with at least 5 years in a technical leadership or architecture role
  • Documented expertise in deep learning frameworks (TensorFlow, PyTorch) and experience with large-scale model training, distributed computing, and MLOps
  • Strong programming skills in Python and familiarity with modern data science tools (e.g., Jupyter, NumPy, Pandas, Scikit-Learn)
  • Proven track record of architecting and deploying AI/ML solutions in cloud environments (AWS, Azure, or GCP), including experience with Databricks, Snowflake, or similar platforms
  • Exceptional communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences
  • Demonstrated leadership in building and mentoring high-performing technical teams

Preferred Qualifications, Capabilities, and Skills:

  • Transformer architectures, reinforcement learning, causal inference, or real-time inference
  • Background in financial services, consumer finance, or regulated industries
  • AWS Certified Machine Learning, Microsoft Certified: Azure AI Engineer, or similar
  • Experience with model governance, regulatory compliance, and risk management in AI/ML
  • Contributions to open-source AI/ML projects or publications in top-tier conferences/journals
 

 

 

 

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  • Role Business Modeling - Applied AI Modeling Executive Director
  • Experience 8-9 years
  • Education PhD
  • Work type On-site
  • Location United States
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JPMorgan Chase
Financial Services & Fintech · 500+ Members · New York, NY, United States

JPMorgan Chase is the largest bank in the United States, based in New York. It serves consumers and small businesses under the Chase brand, and runs investment banking, markets, commercial banking, and asset and wealth management under J.P. Morgan.

All jobs at JPMorgan Chase
Job Overview
Eligibility
United States Right to work in the United States required.
Workplace
On-site
Job Posted:
3 months ago
Job Type
Full Time
Education
PhD
Experience
8-9 years

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