Business Modeling - Applied AI Modeling Executive Director

J.P. Morgan; New York (NY); On-site; USD 175,000 - 230,000; Full time

Job summary

A global financial institution is seeking an Applied AI Modeling Executive Director to lead the development of advanced AI ML solutions. This role involves designing the integration of machine learning architectures and managing a high-performing team. Candidates should have a PhD or MS in a related field, over 10 years of experience in AI/ML deployment, and exceptional communication skills to bridge technical concepts with business needs. The position is located in New York and offers a competitive package.

Qualifications

• 10+ years of hands-on experience in designing and deploying AI/ML models.
• Strong programming skills in Python with familiarity in data science tools.
• Expertise in deploying AI/ML solutions in cloud environments.

Responsibilities

• Architect advanced AI ML solutions that drive business decisions.
• Lead AI talent in adopting new AI techniques for complex problems.
• Develop standards for model oversight and MLOps within teams.

Skills

Deep learning frameworks

Python programming

Advanced AI/ML models

Communication skills

Technical leadership

Education

PhD or MS in Computer Science, Machine Learning, Mathematics, Statistics, Engineering, or Economics

Tools

TensorFlow

PyTorch

AWS

Azure

GCP

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 experiencein 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 Pythonand familiarity with modern data science tools (e.g., Jupyter, NumPy, Pandas, Scikit‑Learn)
• Proven track recordof architecting and deploying AI/ML solutions in cloud environments (AWS, Azure, or GCP), including experience with Databricks, Snowflake, or similar platforms
• Exceptional communication skillswith the ability to explain complex technical concepts to both technical and non‑technical audiences
• Demonstrated leadershipin 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