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Vice President - AI Data Products
senior · Artificial Intelligence
The Chief Data & Analytics Office (CDAO) at JPMorgan Chase propels the firm's data and analytics journey, ensuring data quality and security while leveraging insights for better decision-making. By utilizing AI and machine learning, the CDAO supports commercial goals and strengthens risk management. The Strategy and Execution team defines and implements the CDAO vision, maximizing data value globally through governed practices. Our diverse team values innovation, strategic thinking, and fosters an environment where data-promoten decision-making and creative problem-solving thrive.
As a Vice President – AI Data Products within the CDAO, you will help execute the Firmwide transition towards a Data Product approach as part of our larger data strategy. You are business and technology-savvy, highly solution oriented, and a self-starter who will help implement the approach to define, develop and register data products, so that a collection of curated data for a specific business need can be easily re-used across the organization thereby increasing speed to insight and enabling novel analytics. You will coordinate with the Chief Data Officers of each of Line of Business and Corporate Functions to build a culture of data product management, help planning for hiring and training Data Product Managers across JPMorgan Chase. You will help them to define and execute their data product vision and landscape. Additionally, you will collaborate with other teams within the CDAO organization to execute on the aligned data and analytics strategies.
Job responsibilities:
Execute and refine the approach for data product development at JPMC.
Gather feedback from existing data product teams, and from new pilot implementation to refine the data product guidance for the organization.
Collaborate with Lines of Business and Corporate Functions to determine the high-priority data products they need to build and support for defined business needs, while making them extensible for organization-wide usage.
Ensure data products across the organization are registered consistently in the Firmwide data catalog to ensure they are easily discoverable across the organization.
Lead the creation of strategic reports and white papers that articulate various aspects of organization wide data strategy initiatives, synthesizing inputs from subject matter experts.
Define data product effectiveness metrics (OKRs and KPIs), implement evaluation frameworks, and provide synthesized analysis and strategic insights to senior management and relevant stakeholders.
Communicate complex data concepts and insights to non-technical stakeholders in a clear and actionable manner.
Collaborate with other Firmwide CDAO teams to refine existing data strategies and define new approaches to meet the evolving needs of the business.
Serve as a trusted advisor to data leaders across the organization, driving adoption of best practices through collaboration.
Required qualifications, capabilities and skills:
5+ years of relevant experience in data management, data engineering, artificial intelligence and machine learning domains.
3+ years of experience either as a product manager, product designer, engineer, data analyst, data scientist, or user researcher.
Demonstrated ability to solve complex problems with multiple constraints, employing sound judgment to assess risks and articulate solutions through well-structured, data-driven written narratives.
Proven ability to engage with engineers, designers, and company leaders in a constructive and collaborative relationship.
Ability to think innovatively while applying a rigorous, data-led disciplined approach to data product management and innovation.
Exceptional analytical, problem solving, communication and presentation skills.
Ability to articulate business needs to technical teams and convey technical issues to business leadership.
Strong attention to detail and quality, with excellent written and verbal communication.
Preferred qualifications, capabilities and skills:
Familiarity with the financial services industry
Proficiency in data management tools.
Familiarity with common cloud-native data analysis platforms such as Databricks, Snowflake, Starburst
Familiarity with data governance and regulatory requirements (e.g. BCBS 239, GDPR, CCPA).
Proven ability to lead teams, manage stakeholder expectations, and partner with cross functional teams.
Knowledge and experience of building or managing data products and datasets delivering business needs