Applied AI ML Vice President

JPMorgan Chase JPMorgan Chase · Banking · Jersey City, NJ +1 · Corporate Sector

This Vice President, Data Scientist role at JPMorgan Chase focuses on developing and implementing advanced AI solutions within Risk Management and Compliance. The role involves designing and deploying multi-agent systems, implementing drift monitoring and retraining processes, defining evaluation frameworks for AI systems, and integrating AI into existing workflows. The position requires a strong track record in deploying and managing AI/ML models in an enterprise setting, experience with agent orchestration frameworks, and a scientific mindset.

What you'd actually do

  1. Design and implement multi-agent systems, including orchestration layers that coordinate specialized agents, manage task routing, and integrate human-in-the-loop (HITL) controls.
  2. Define and implement evaluation frameworks for AI/agentic systems, including prompt quality, agent performance, and business outcome metrics.
  3. Design, build, and deploy impactful AI and data-driven applications using cloud, data mesh, and knowledge base technologies such as centralized repositories, semantic search, and automated information retrieval systems that organize, store, and provide easy access to critical business data and insights.
  4. Implement robust drift monitoring and model retraining processes to maintain accuracy and performance through ongoing performance monitoring.
  5. Demonstrate proficiency in the end-to-end model development lifecycle, including planning, execution, continuous improvement, risk management, and ensuring solutions are scalable and aligned with business objectives.

Skills

Required

  • 6+ years of experience in data science, analytics or a related field.
  • Deploying, operationalizing, and managing AI, ML, and advanced analytics models in a large-scale enterprise environment.
  • AI/ML algorithms, statistical modeling, and scalable data processing pipelines.
  • A/B experimentation and the ability to develop and debug production-quality code.
  • Strong written and verbal communication skills.
  • Scientific mindset with the ability to innovate and work both independently and collaboratively.
  • Ability to thrive in a matrix environment and build partnerships.
  • Building and deploying multi-agent systems, including use of orchestration frameworks (e.g. LangGraph, ADK), agent design patterns, and production-grade system integration.

Nice to have

  • Advanced degree (Master’s or Ph.D.) in Data Science, Computer Science, Mathematics, Engineering, or a related field.

What the JD emphasized

  • Proven track record of deploying, operationalizing, and managing AI, ML, and advanced analytics models in a large-scale enterprise environment.
  • Proven experience building and deploying multi-agent systems, including use of orchestration frameworks (e.g. LangGraph, ADK), agent design patterns, and production-grade system integration.

Other signals

  • multi-agent systems
  • orchestration layers
  • evaluation frameworks
  • AI/ML algorithms
  • deploying, operationalizing, and managing AI, ML, and advanced analytics models