Product Manager - Data AI

As a Data for AI Product Manager, you will play a pivotal role in simplifying the data access and integration experience for data scientists during model training, experimentation and serving. This involves building a seamless end‑to‑end experience for data scientists right from data discovery to access to integration. We're looking for someone who leads with problems, not solutions—who deeply understands user pain points, identifies high‑impact opportunities, and builds scalable platform capabilities that enable thousands of data practitioners to move faster.

• Define strategy and roadmap for data access within ML training and serving platforms (Sage Maker, EMR, Databricks)
• Define success metrics tied to business impact: reduced time-to-model, increased adoption, improved governance
• Take end‑to‑end ownership from problem discovery through delivery, adoption, and iteration

• Design composable, reusable solutions that integrate seamlessly with the broader CDAO platform ecosystem.
• Balance short‑term user needs with long‑term platform scalability and extensibility

• Partner with engineering teams to translate user problems into technical solutions—APIs, SDKs, infrastructure
• Write detailed product requirements that engineers can execute against, along with technical product documentation for customers
• Make informed trade‑offs between technical complexity, user experience, and time‑to‑market

• Spend time with data scientists, ML engineers, and data engineers to understand their workflows and pain points
• Partner with UX research teams for usability testing, rapid prototyping, and user validation
• Build delightful experiences that balance functional and non‑functional requirements

• Proactively identify opportunities to streamline workflows and accelerate model development
• Influence cross‑functional stakeholders (engineering, architecture, data science, governance, UX) to drive outcomes
• Learn and adapt in a dynamic and fast‑paced environment

• 6+ years in technical product management delivering platform products or developer tools, or infrastructure solutions from ideation to production
• Proven track record of impact:
  Built products that measurably improved user workflows, increased adoption, or reduced friction
• Platform thinking mindset:
  Design for reusability, composability, and scale—not one‑off solutions
• Technical depth:
  Practical knowledge of industry‑wide training and serving platforms such as AWS Sage Maker, EMR, etc.
• Strong communication:
  Translate technical complexity into clear narratives for engineers and executives
• Prioritization skills:
  Balance competing demands by understanding business impact, user value, and technical feasibility

• Experience in financial services or highly regulated industries
• Familiarity with data platform technologies: data catalogs, feature stores, governance frameworks, data quality tools
• Knowledge of ML lifecycle tools: feature engineering, model training, serving, monitoring, observability
• Experience with open‑source and commercial platforms:
  Snowflake, Databricks, Airflow, Kafka

• Work on firm‑wide platforms used by thousands of data scientists, ML engineers, and analysts across JPMC
• Shape the future of AI/ML and data infrastructure at one of the world's largest financial institutions

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first‑class business in a first‑class way approach to serving clients drives everything we do. We strive to build trusted, long‑term partnerships to help our clients achieve their business objectives.

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.