Digital & Platform Services - Head of Applied AI & Data Transformation for Core Data - Executive Director

JPMorgan Chase & Co.London, EnglandOn-siteFull-timeStaff, 8–12 yearsListed 44 minutes ago

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About this role

Short Job Description:
Lead the strategic transformation of Core Data within the Commercial & Investment Bank, driving AI-readiness, automation, and data quality to enable business growth and operational excellence.

Introductory Marketing Language:
Join us at the forefront of data innovation within the Commercial & Investment Bank. As Head of Applied AI & Data Transformation for Core Data, you will shape the future of how we manage, automate, and scale our data capabilities. This is a unique opportunity to drive impactful change, influence senior leadership, and deliver solutions that empower both people and machines. You will work in partnership with technology and business teams to unlock the full potential of our data assets. If you are passionate about data strategy and transformation, this role offers the platform to make a significant difference.

Job Summary:
Core Data encompasses the reference and common data domains that underpin downstream processing across front-to-back workflows. As an Executive Director, the Head of Applied AI & Data Transformation for Core Data in the Commercial & Investment Bank, you will define and execute the strategy for managing, automating, and scaling Core Data capabilities. You will partner closely with Technology, Business, and Operations to ensure data is discoverable, consumable, and fit for purpose. You will lead a high-calibre team, drive AI-readiness, and champion data quality, transparency, and access. Together, we will create a cohesive operating model that delivers value across Markets, Securities Services, and beyond.

Job Responsibilities:

- Drive the strategic direction and alignment of Core Data with the CIB Data AI-Readiness framework
- Define and implement an executable roadmap for agent-ready Core Data, spanning discoverability, entitlements, and semantic context
- Partner with Technology to make Core Data assets discoverable and consumable by both people and machines
- Ensure core data assets are registered and described in the Compass catalogue and integrated into Fusion
- Shape the exposure of reference data through distribution APIs to meet CIB consumption patterns
- Establish semantic layers to provide business meaning, definitions, and relationships for AI and agentic consumers
- Identify and eliminate complexity, duplication, and manual handling in Core Data processes
- Develop independent data quality assessment capabilities, establishing transparent, evidence-based reporting
- Evaluate, design, and prototype automation approaches, including rules-based, AI/ML, and agentic solutions
- Reduce access friction and bottlenecks, enabling self-service for Business and Operations users
- Build strong partnerships across Reference Data Product Owners, Operations, CIB CDAO Teams, Corporate Technology, and senior leadership
- Lead and scale a high-performing team as business demand grows

Required Qualifications, Capabilities, and Skills:

- Proven experience leading data strategy, transformation, or a comparable senior business role within financial services or another highly regulated, complex environment
- Deep understanding of core data domains and their role in enabling downstream processing across front-to-back workflows
- Familiarity with data cataloguing, metadata, and API design concepts
- Ability to translate complex data concepts into clear, compelling narratives for diverse audiences
- Experience designing or overseeing automation solutions applied to data management and operational workflows
- Track record of delivery through influence and effective partnership across Business, Operations, Functions, and Technology stakeholders
- Entrepreneurial mindset with the ability to build from the ground up, assess opportunities, and scale capabilities
- Team leadership and people management experience, including scaling and developing high-performing teams

Preferred Qualifications, Capabilities, and Skills:

- Experience with AI/ML and agentic approaches in data management
- Knowledge of data quality assessment methodologies
- Familiarity with regulatory requirements in financial services
- Strong stakeholder management and communication skills
- Experience in greenfield environments
- Ability to drive change in platforms owned by others
- Advanced degree in a relevant field