Vice President, Data Strategy for AI

Help accelerate Asset Management’s data strategy with a role that directly enables high-impact analytics and artificial intelligence use cases. You will strengthen metadata foundations and support the development of ontologies that improve data discoverability, usability, and governance. This is a hands-on opportunity to work across business stakeholders, data owners and custodians, and technology teams to translate real needs into measurable deliverables. You will partner closely with the Artificial Intelligence Data Strategy Lead while helping unblock delivery across multiple work streams. Job Summary As a Vice President - AI Data Strategy in Asset Management Data Strategy & Platform, you will drive artificial intelligence data readiness by strengthening metadata, documentation, quality expectations, and access and control readiness. You will collaborate with business consumers, data owners and custodians, product partners, and technology teams to translate priority use cases into clear data, metadata, and semantic deliverables. You will help shape and promote the adoption of Asset Management artificial intelligence ontologies so teams can use data more consistently across domains and data products. Job Responsibilities: Execute artificial intelligence data readiness work streams to strengthen metadata robustness, documentation, quality expectations, access readiness, and controls Partner with business consumers and analytics users to understand priority use cases and translate them into clear readiness requirements and deliverables Assess data fitness-for-purpose with data owners and custodians against business and artificial intelligence use needs Support the design and adoption of Asset Management artificial intelligence ontologies to promote consistent usage across data domains and data products Coordinate across business, product, technology, and data stakeholders to unblock delivery Manage dependencies, risks, issues, and delivery plans across multiple work streams Ensure deliverables meet documentation, governance, and control standards Analyze data to identify trends and root causes, and synthesize actionable insights to inform prioritization and decisions Use agile tools (for example, Jira and Confluence) to manage work, report status, and increase transparency to stakeholders and governance forums Improve data operating model practices by identifying duplication and consolidation opportunities Required qualifications, capabilities, and skills: 7+ years of relevant experience in data analysis, data delivery, data management, data strategy or transformation roles in complex, matrixed environments Demonstrated ability to deliver outcomes with minimal supervision, operate effectively with ambiguity, and “join the dots” across business, data, and technology Strong stakeholder engagement skills, including influencing without authority and translating business needs into data/metadata/semantic requirements Hands-on understanding of data quality and metadata management (e.g., definitions, ownership, usage context), with comfort working in detail with datasets (SQL and/or Python) Risk and control awareness, including alignment to regulated environment requirements Practical experience with agile methodologies and tools (JIRA, Confluence, Kanban), with disciplined planning, status reporting, and issue/risk management Preferred qualifications, capabilities, and skills: Experience in Asset Management and familiarity with investment and/or client data domains Familiarity with data product practices such as data contracts, lifecycle management, and product telemetry Exposure to semantic modeling approaches (ontologies/taxonomies/controlled vocabularies) used to enable analytics or AI use cases Bachelor’s degree or equivalent experience required; advanced degree or relevant certifications (e.g., Agile, PMP) a plus