VP, Data Strategy & Governance

Lincoln Financial•Radnor, PA

1d•Hybrid

About The Position

Lincoln Financial is building a strong, enterprise-scale foundation to enable AI-driven transformation across the organization. We are seeking an VP, Data Strategy & Governance to play a critical role in shaping how data is governed, trusted, and leveraged to power analytics and AI products. This role sits within the AI, Data & Analytics organization and is responsible for establishing and operationalizing Lincoln’s enterprise data governance framework, data quality programs, and data standards. You will operate at the intersection of AI strategy, business partnership, and governance, ensuring enterprise data is discoverable, reliable, compliant, and AI ready. Reporting to the Chief Data & AI Engineering Officer, you will partner closely with the Head of AI Product & Delivery, the CIO organization, and senior business leaders. This is a highly visible, build from the ground up opportunity with strong executive sponsorship.What you'll be doingData Strategy & Governance Framework • Define and execute an enterprise data strategy aligned to Lincoln’s AI transformation and business objectives• Establish a comprehensive data governance framework, including policies, standards, roles, and operating models that support responsible and scalable AI• Create and chair an enterprise data governance council with representation across AI, Engineering, CIO, and business units• Define clear data ownership and accountability for key enterprise domains (e.g., customer, policy, claims, financial, actuarial)• Develop AI specific data governance policies, including fairness, bias detection, explainability, and lineage requirements• Partner closely with the CIO organization to align enterprise data standards with regulatory and compliance requirements (SOX, GLBA, CCPA, state insurance regulations)Data Quality Management • Define enterprise data quality standards, metrics, and acceptance criteria to ensure AI model reliability• Establish data quality measurement and monitoring frameworks for AI training and production datasets• Implement data certification processes for AI training, testing, and production data products• Lead root cause analysis for data quality issues impacting AI model performance or delivery timelines• Define and manage data quality SLAs for high impact AI use casesLogical Data Architecture & Standards • Design logical enterprise data models, semantic layers, and domain based data architectures optimized for AI consumption• Establish and maintain a business friendly enterprise semantic layer for analytics and AI teams• Develop and govern enterprise data dictionaries, business glossaries, and taxonomies• Define canonical data definitions to resolve cross system and cross business inconsistencies• Establish data contracts and interface standards between domains to ensure reliable AI data consumptionData Products, Catalog & Self Service• Define enterprise data product strategy aligned to the AI product roadmap• Implement a data catalog strategy enabling discovery of training data, features, and production datasets• Enable a data marketplace for AI teams and business users to discover and request data assets• Partner on enterprise data literacy initiatives across executives, product managers, and technical teams• Build communities of practice across data, AI, and business stakeholdersBusiness Partnership & Value Realization • Serve as a strategic advisor to senior business leaders (e.g., Underwriting, Claims, Actuarial)• Translate business strategies into data and AI requirements• Identify opportunities to monetize proprietary data assets• Measure and communicate business value delivered through data and AI initiatives

Requirements

10+ years of experience in data management and strategy, with 5+ years focused on data governance, architecture, or AI enablement
Proven success establishing enterprise data governance and data quality programs at scale
Deep expertise in logical data modeling, metadata management, and semantic architectures
Experience enabling AI/ML products from experimentation through production
Strong executive presence and ability to influence senior stakeholders
Background in highly regulated industries (insurance, banking, financial services)
Hands on experience with data catalogs, self service analytics, and data democratization
Bachelor’s degree required; MBA or Master’s degree preferred

Nice To Haves

Insurance domain expertise (policy, claims, actuarial, billing data)
ML/AI data platforms (feature stores, training pipelines, monitoring)
Data mesh or domain driven data product architectures
Experience with Collibra, Alation, Atlan, or similar platforms
Analytics engineering tools (dbt, Looker, modern semantic layers)
Knowledge graphs and semantic web technologies (RDF, OWL, SPARQL)

Responsibilities

Define and execute an enterprise data strategy aligned to Lincoln’s AI transformation and business objectives
Establish a comprehensive data governance framework, including policies, standards, roles, and operating models that support responsible and scalable AI
Create and chair an enterprise data governance council with representation across AI, Engineering, CIO, and business units
Define clear data ownership and accountability for key enterprise domains (e.g., customer, policy, claims, financial, actuarial)
Develop AI specific data governance policies, including fairness, bias detection, explainability, and lineage requirements
Partner closely with the CIO organization to align enterprise data standards with regulatory and compliance requirements (SOX, GLBA, CCPA, state insurance regulations)
Define enterprise data quality standards, metrics, and acceptance criteria to ensure AI model reliability
Establish data quality measurement and monitoring frameworks for AI training and production datasets
Implement data certification processes for AI training, testing, and production data products
Lead root cause analysis for data quality issues impacting AI model performance or delivery timelines
Define and manage data quality SLAs for high impact AI use cases
Design logical enterprise data models, semantic layers, and domain based data architectures optimized for AI consumption
Establish and maintain a business friendly enterprise semantic layer for analytics and AI teams
Develop and govern enterprise data dictionaries, business glossaries, and taxonomies
Define canonical data definitions to resolve cross system and cross business inconsistencies
Establish data contracts and interface standards between domains to ensure reliable AI data consumption
Define enterprise data product strategy aligned to the AI product roadmap
Implement a data catalog strategy enabling discovery of training data, features, and production datasets
Enable a data marketplace for AI teams and business users to discover and request data assets
Partner on enterprise data literacy initiatives across executives, product managers, and technical teams
Build communities of practice across data, AI, and business stakeholders
Serve as a strategic advisor to senior business leaders (e.g., Underwriting, Claims, Actuarial)
Translate business strategies into data and AI requirements
Identify opportunities to monetize proprietary data assets
Measure and communicate business value delivered through data and AI initiatives

Benefits

Clearly defined career tracks and job levels, along with associated behaviors for each of Lincoln's core values and leadership attributes
Leadership development and virtual training opportunities
PTO/parental leave
Competitive 401K and employee benefits
Free financial counseling, health coaching and employee assistance program
Tuition assistance program
Work arrangements that work for you
Effective productivity/technology tools and training

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume