About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 384 open roles on FindRole.

Listed pay typically runs $152,000–$215,000 across 202 roles with salary data.

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At a glance

TL;DR · Senior Product Associate

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The Senior Product Associate role at J.P. Morgan Chase involves contributing to the Corporate & Investment Banking Planning & Analysis Data Transformation and Innovation team by developing and executing data and product strategies that enhance business reporting and analytics. Day-to-day responsibilities include conducting user interviews, prioritizing needs, testing ideas, and converting insights into scalable solutions using AI-enabled capabilities such as multi-agentic workflows and Model Context Protocol (MCP). The ideal candidate will have a strong understanding of financial data models, experience with cloud-based platforms like AWS and Databricks, and proficiency in SQL for data analysis. Additionally, familiarity with business intelligence tools and emerging data consumption patterns is essential, along with the ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders.

Skills

AWS Databricks AI/ML SQL BI tools MCP Kubernetes CI/CD Python PostgreSQL

What you'll do

Develops and executes data and product strategy to deliver value through reporting and analytics.
Conducts user interviews and prioritizes needs to create scalable solutions for end users.
Designs AI-enabled product capabilities, including multi-agentic workflows and Model Context Protocol (MCP).
Defines data requirements and acceptance criteria based on understanding of financial data models.
Collaborates with teams to improve data consumption patterns and influence decision-making through analytics.

What we're looking for

Demonstrated ability to formulate and execute data and product strategy.
Strong understanding of financial data models and BI tools like SQL for analysis.
Experience with AI/ML technologies, including large language models and multi-agentic workflows.
Comfort operating in complex, highly governed environments within the financial services industry.
Knowledge of cloud-based data platforms such as AWS and Databricks.
Excellent communication skills to convey complex data concepts to various stakeholders.