VP, AI Data Strategy & Program Management

BP&C•New York City, NY

1d•Onsite

About The Position

Clearbrook is seeking a hands-on, execution-focused Vice President, Data & AI Strategy to operationalize the enterprise’s data and AI capability. Reporting to the SVP, Data & AI Strategy, this role translates enterprise strategy and governance frameworks into working processes, tooling, and day-to-day practices across business domains. The VP works with business stakeholders, data stewards, analysts, data scientists, and engineers to implement governance standards, integrate external data, mature master data capabilities, and manage the data and AI portfolio’s schedule and visibility to leadership. This is a 100% in-office position. Employees may apply from any Clearbrook office and remain in their current location, but must work on-site at a designated company office during standard business hours. The position is full-time and exempt.

Requirements

At least 7 years of experience in data strategy, data governance, data management, or a related discipline.
3–5+ years of people leadership experience managing teams or cross-functional workstreams.
Demonstrated experience delivering data governance or data management programs at enterprise scale.
Working knowledge of master data management, data architecture, and modern data platforms.
Ability to turn strategic direction into practical, repeatable processes that teams adopt.
Strong stakeholder management skills across business and technical audiences.
Hands-on experience with data governance and data management tooling.
Proven ability to drive complex, cross-functional programs to completion.
Clear communication, strong organizational discipline, and comfort operating with a light footprint.
Must be legally authorized to work in the United States; employment visa sponsorship is not available.
Must be able to work on-site at a designated company office during standard business hours.

Nice To Haves

Experience within insurance, financial services, or a related industry.

Responsibilities

Implement the enterprise data governance framework and operating model, adapting it to individual business domains.
Maintain and enforce data ownership assignments, standards, best practices, and quality processes; facilitate prioritization, escalate gaps and conflicts, and drive resolution.
Drive day-to-day adoption of governance practices within business domains, including Policy, Claims, Finance, Pricing, and Compliance.
Work with data stewards, engineers, and analysts to build and maintain the centralized data dictionary and standardized business definitions.
Embed governance checkpoints into existing business and technology workflows without adding friction to delivery.
Execute the enterprise external data strategy, including intake, evaluation, and onboarding of new data sources.
Manage day-to-day relationships with data providers and support provider selection, negotiation, and renewal decisions.
Coordinate with data engineering to integrate external data into platforms and cloud environments on committed timelines.
Ensure external data assets are governed, documented, and monitored for quality and usage after onboarding.
Build and operate master data management capabilities for assigned core data domains under the enterprise MDM strategy.
Implement master data stewardship and lifecycle processes; run matching, survivorship, and remediation workstreams.
Partner with underwriting, claims, finance, and AI teams to connect master data capabilities to live use cases.
Manage programs for strategic data and AI portfolio initiatives, including planning, tracking, and delivery.
Operate standardized intake, prioritization, and delivery frameworks, and recommend refinements based on results.
Produce regular status, risk, and outcome reporting for leadership and enterprise stakeholders.
Coordinate cross-functional execution across business, IT, data engineering, analytics, and data science teams.
Surface risks, dependencies, and resourcing constraints early.