VP, Reinsurance Data, Analytics & Performance Strategy

Everest

New Jersey

On-site

USD 201,000 - 245,000

Full time

14 days+

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Benefits offered by this job

Health insurance

401k match

Retirement savings plan

Paid holidays

PTO

Job summary

Everest is seeking aSenior Vice President of Reinsurance Data, Analytics & Business Performance to shape data strategy across the Reinsurance organization in Warren, NJ. You will lead analytics, reporting, and governance initiatives, partnering with Underwriting, Claims, Finance, and Technology to deliver scalable data solutions and data-enabled decisions.

The role emphasizes data governance, AI-enabled insights, and strong stakeholder management to align data maturity with business outcomes.

Qualifications

Bachelor's degree in Business, Finance, Economics, Analytics, Information Systems, Mathematics, Data Science, or a related discipline; advanced degree preferred.
12+ years of progressive experience in data & analytics, business intelligence, performance management, data strategy, or related leadership roles.
Deep Reinsurance industry experience with strong knowledge of underwriting, claims, finance, operations, portfolio management, and performance metrics.
Demonstrated experience leading enterprise reporting, analytics, and business intelligence functions that support business and executive decision-making.
Advanced Power BI expertise, including dashboard design, data modeling, KPI frameworks, visualization best practices, and self-service analytics enablement.
Proven experience partnering with business and technology teams to define requirements, prioritize initiatives, and deliver data, reporting, and analytics capabilities.
Strong understanding of data governance, data quality, metadata management, and enterprise data management principles.
Experience establishing data stewardship, ownership, and data quality processes across multiple business domains.
Familiarity with modern cloud-based data and analytics platforms and emerging AI capabilities relevant to analytics, reporting, and decision support.
Strong understanding of Reinsurance underwriting economics and performance metrics, including premium growth, loss ratio, expense ratio, combined ratio, portfolio profitability, and return on capital.
Strong stakeholder management skills with the ability to influence and build relationships across senior executives, business leaders, and technology teams.
Demonstrated success leading and developing high-performing teams.
Excellent communication, presentation, and storytelling skills, with the ability to translate complex data into actionable business insights and recommendations.

Responsibilities

Develop and execute the Reinsurance data, analytics, reporting, and business performance strategy aligned with business objectives and enterprise data priorities.
Partner with senior leaders across Underwriting, Claims, Finance, Operations, and Executive Management to identify priorities and deliver data-driven solutions that improve business outcomes.
Own the Reinsurance data and analytics roadmap, translating business strategy into a prioritized portfolio of data, reporting, and analytics initiatives.
Collaborate with Technology and Enterprise Data & Analytics teams to define requirements, prioritize investments, and deliver scalable data and analytics capabilities.
Lead the development and continuous enhancement of operational, management, and executive reporting solutions, ensuring stakeholders have access to timely and actionable insights.
Establish and oversee key performance indicators, scorecards, dashboards, and performance measurement frameworks, including governance of KPI definitions, reporting standards, and methodologies.
Provide leadership and direction for Power BI capabilities, including reporting standards, data modeling, visualization best practices, and self-service analytics adoption.
Define and advance Reinsurance data governance, data stewardship, and ownership practices to improve accountability, consistency, and trust in enterprise data.
Establish and mature data quality capabilities, including critical data element management, data quality metrics, monitoring, issue remediation, and continuous improvement processes.
Evaluate and implement opportunities to leverage AI and emerging analytics capabilities to improve access to information, enable natural language querying, and deliver AI-driven insights to business users.
Partner with business stakeholders to identify opportunities for process improvement, operational efficiencies, portfolio optimization, and business growth through analytics.
Communicate business performance, key insights, opportunities, and risks through executive presentations, dashboards, and leadership forums.
Lead, develop, and mentor a high-performing team while fostering a culture of accountability, business partnership, innovation, and continuous improvement.