Business Modeling - Applied AI Modeling Executive Director

JPMorgan Chase JPMorgan Chase · Banking · New York, NY +1 · Consumer & Community Banking

Executive Director role focused on architecting and leading the development of next-generation AI/ML solutions for credit card and banking business decisions, managing the full AI/ML lifecycle from design to production deployment, and leading a team of AI/ML scientists and engineers. Emphasizes deep learning, advanced modeling, MLOps, and cloud-native deployment within a regulated financial services environment.

What you'd actually do

  1. 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
  2. Partner with the Business Stakeholders and break down silos to translate business needs into technical solutions while managing the full AI/ML lifecycle
  3. 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
  4. 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
  5. 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

Skills

Required

  • 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
  • at least 5 years in a technical leadership or architecture role
  • Documented expertise in deep learning frameworks (TensorFlow, PyTorch)
  • experience with large-scale model training, distributed computing, and MLOps
  • Strong programming skills in Python
  • 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)
  • experience with Databricks, Snowflake, or similar platforms
  • Exceptional communication skills
  • Demonstrated leadership in building and mentoring high-performing technical teams

Nice to have

  • Transformer architectures
  • reinforcement learning
  • causal inference
  • 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

What the JD emphasized

  • architect the development of next-generation AI ML solutions
  • scaling robust AI/ML systems
  • production environments
  • full AI/ML lifecycle
  • governance and regulatory expectations
  • regulatory compliance

Other signals

  • architecting and deploying AI/ML solutions
  • leading a team of experts
  • full AI/ML lifecycle
  • production environments