[Hiring] VP Enterprise Intelligence @Your Journey Starts Here

Role Description

Do you combine enterprise leadership, data fluency, and the ability to turn intelligence into measurable business outcomes? Are you energized by building strong teams? If so, this role offers the opportunity to shape the intelligence agenda for US Life Insurance.

As VP of Enterprise Intelligence, reporting to the CTO, US Life Insurance, you will assume leadership of the existing Data Engineering and AI/ML teams and establish a unified enterprise intelligence capability. You will be accountable for dramatically improving carrier reporting and analytics across US Life Insurance, creating trusted data foundations, decision-ready insights, and responsible AI capabilities that improve how the business operates and grows.

Your Mandate

• Enterprise intelligence strategy: Define and execute a multi-year strategy for enterprise data, reporting, analytics, and AI/ML aligned with US Life Insurance priorities.
• Trusted data foundation: Strengthen data engineering, architecture, governance, quality, lineage, integration, and delivery practices so critical information is reliable, reusable, secure, and accessible.
• Carrier reporting transformation: Modernize management, operational, distribution, customer, and regulatory reporting by improving consistency, timeliness, usability, and ownership.
• Analytics at the point of decision: Move the organization along the journey from retrospective reporting toward forward-looking analytics, decision support, and measurable business insight.
• Responsible AI at scale: Build a disciplined AI/ML portfolio, including practical use cases, reusable capabilities, model lifecycle controls, and responsible adoption in partnership with business, risk, legal, and compliance stakeholders.
• High-performing organization: Unify and develop the Data Engineering and AI/ML teams around clear products, standards, accountabilities, career paths, and outcomes.

Key Responsibilities

• Own the vision, roadmap, operating model, and investment priorities for enterprise intelligence across US Life Insurance.
• Establish a business-aligned portfolio of data products, analytics capabilities, reporting solutions, and AI/ML use cases with transparent value, ownership, and delivery commitments.
• Partner with executives and functional leaders to identify critical decisions, define common metrics, and translate business needs into scalable intelligence capabilities.
• Simplify and rationalize fragmented reports, dashboards, data pipelines, and analytical tools while preserving essential needs.
• Create standards for enterprise metrics, semantic definitions, master and reference data, metadata, lineage, data quality, and accountable stewardship.
• Ensure data and AI solutions meet expectations for security, privacy, compliance, resilience, model risk, auditability, and third-party oversight.
• Guide the modernization of data platforms and integration patterns, balancing speed, maintainability, cost, interoperability, and reuse.
• Develop an enterprise reporting experience that enables leaders to move from summary measures to actionable drivers and appropriately governed detail.
• Define and communicate outcome-based measures for adoption, data quality, delivery speed, platform reliability, reporting efficiency, insight utilization, and business value.
• Build data literacy and responsible AI fluency across the organization through communication, enablement, communities of practice, and hands-on partnership.

What Success Looks Like

• Leaders and managers have timely access to consistent, trusted, and decision-ready information.
• Critical enterprise metrics have clear definitions, accountable owners, traceable sources, and visible quality expectations.
• Reporting is easy to use and maintain, with reduced duplication, manual effort, reconciliation, and time-to-insight.
• Data Engineering and AI/ML operate as an integrated, business-focused organization with clear priorities and dependable delivery.
• AI/ML investments are governed responsibly, adopted meaningfully, and connected to measurable outcomes.
• The intelligence portfolio is transparent, financially disciplined, scalable, and aligned to the highest-value business opportunities.

Qualifications

• Bachelor’s degree in computer science, data science, engineering, information systems, analytics, business, or a related discipline; advanced degree preferred.
• Significant progressive leadership experience in enterprise data, analytics, reporting, AI/ML, or related technology functions, including leadership of leaders and multidisciplinary teams.
• Demonstrated success defining and executing enterprise data and analytics strategy in a complex, regulated organization.
• Practical understanding of modern data architecture, cloud data platforms, integration, data products, governance, DataOps, MLOps, and the AI/ML lifecycle.
• Executive presence and strong communication skills, with the ability to simplify complex topics and build alignment across diverse stakeholders.
• Proven ability to lead transformation, influence without direct authority, resolve competing priorities, and sustain adoption through change.
• Strong talent leadership, including the ability to attract, develop, engage, and retain specialized data and AI professionals.
• Knowledge of life insurance business models, products, distribution, underwriting, policy administration, actuarial, claims, finance, and regulatory reporting is a plus.

Benefits

• Compensation: $227K - $280K
• Medical Insurance: Choose from a variety of plans to fit your healthcare needs.
• Dental Insurance: Coverage for preventive, basic, and major dental services.
• Employer-Paid Vision: Comprehensive eye care coverage at no cost to you.
• Employer-Paid Basic Life and AD&D Insurance: Peace of mind and additional protection.
• Employer-Paid Short-Term and Long-Term Disability Insurance: Financial support in case of illness or injury.
• 401(k) Plan: Save for your future with a company match to help you grow your retirement savings.
• PTO and Sick Time accrue each pay period: Take time off when you need it.
• Annual Bonus Program: Performance-based bonus to reward your hard work.
• Remote work is not available in the following States: California, Colorado, Connecticut, and New York.