Applied AI ML Vice President

JPMorgan Chase & Co.•Jersey City, NJ

5h•$164,350 - $260,000

About The Position

As a Vice President, Data Scientist in the Data Science team, you will help us shape the future of financial services by developing and implementing advanced AI solutions. You will collaborate with product, engineering, and business partners to create impactful, scalable tools that drive real business value. In this role, you will have the opportunity to experiment, learn, and innovate alongside a diverse team, leveraging your expertise in data science and finance. Together, we will deliver solutions that transform how we operate and serve our clients. Join us to make a meaningful difference and grow your career in a dynamic, inclusive environment.

Requirements

Minimum 6+ years of experience in data science, analytics or a related field.
Proven track record of deploying, operationalizing, and managing AI, ML, and advanced analytics models in a large-scale enterprise environment.
Experience in AI/ML algorithms, statistical modeling, and scalable data processing pipelines.
Experience with A/B experimentation and the ability to develop and debug production-quality code.
Strong written and verbal communication skills, with the ability to convey technical concepts and results to both technical and business audiences.
Scientific mindset with the ability to innovate and work both independently and collaboratively within a team.
Ability to thrive in a matrix environment and build partnerships with colleagues at various levels and across multiple locations.
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.

Nice To Haves

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

Responsibilities

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.
Design and implement multi-agent systems, including orchestration layers that coordinate specialized agents, manage task routing, and integrate human-in-the-loop (HITL) controls.
Implement robust drift monitoring and model retraining processes to maintain accuracy and performance through ongoing performance monitoring.
Define and implement evaluation frameworks for AI/agentic systems, including prompt quality, agent performance, and business outcome metrics.
Collaborate with senior leaders to re-engineer processes by embedding AI into current workflows, driving change and efficiency.
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.
Integrate advanced analytics models and applications into operational workflows to ensure business value and adoption.
Communicate analytical findings and recommendations to senior leadership.