Vice President, Data and Analytics

Carolina Casualty is a member company of W. R. Berkley Corporation, an insurance holding company that is among the largest commercial lines insurance writers in the United States. We specialize in liability, physical damage, cargo and other insurance solutions for the commercial auto markets including trucking, public transportation and others. 

We maintain some of the lowest claim adjuster pending claim counts in the industry. Our adjusters are part of a culture that emphasizes inclusion, collaboration, innovation, and team. Our culture is one where your work is recognized and appreciated. If you want to contribute to an organization where you matter and where you can make a difference, then search no further. 

The company is an equal opportunity employer.

CCIC is seeking an experienced data and analytics leader to serve as VP, Data & Analytics — a newly created, high-impact role within the enterprise.

Candidate must work out of the Jacksonville, FL OR Boston, MA OR North Royalton, OH office

Key Functions will include but not be limited to:

Operating Unit Onboarding & Platform Adoption

• Lead the structured onboarding of CCIC to the Helix enterprise data platform, including data ingestion, transformation, and consumption layer buildout.
• Serve as the primary Data and Analytics (DNA) point of contact for technology and business stakeholders throughout the onboarding lifecycle.
• Develop and manage onboarding playbooks and project plans tailored to data landscape, technical readiness, and business priorities.
• Coordinate with corporate DNA platform and engineering teams to ensure requirements are represented in platform roadmap prioritization.

Gap Assessment & Data Maturity

• Conduct structured data maturity and gap assessments, spanning data sources, data quality, governance readiness, reporting capabilities, and analytical tooling.
• Document current-state data architecture and identify gaps relative to Helix platform standards and enterprise data governance requirements.
• Develop prioritized remediation roadmaps; defining short-, medium-, and long-term milestones for data modernization.
• Identify and escalate data inconsistencies, duplicate data products, or integration risks that affect segment-level reporting and analytics.

Data Governance & Standards Alignment

• Champion adoption of enterprise data governance policies, data quality standards, metadata management, and lineage practices within the commercial trucking segment.
• Partner with other OUs data stewards and corporate governance teams to define commercial trucking data domains, ownership, and stewardship responsibilities.
• Ensure all data products and pipelines developed within or for the trucking segment adhere to Helix platform standards, security requirements, and compliance obligations.
• Drive consistent data definitions and business glossary alignment to enable accurate segment-level analytics and reporting.

Analytics Enablement & Business Alignment

• Collaborate with key functional areas including but not limited to underwriting, claims, finance, and operations leaders to understand their analytical needs and translate them into platform-enabled data products and dashboards.
• Enable self-service analytics capabilities for trucking segment business users by business needs to Helix's BI and analytics tooling.
• Identify opportunities for cross-collaboration on analytics, benchmarking, and shared data products that generate competitive insight for the commercial trucking segment.
• Collaborate with telematics product owners to develop and execute telematics strategy across key functional areas
• Support the development of advanced analytics, predictive modeling, and AI/ML use cases relevant to commercial trucking underwriting performance, loss analysis, and risk selection.

Delivery Organization & Roadmap Management

• Organize and manage the delivery backlog for commercial trucking data work, ensuring alignment between OU demand and corporate DNA capacity and priorities.
• Facilitate regular cadences with OU stakeholders and DNA teams to review progress, resolve blockers, and adjust delivery plans as needed.
• Define and track KPIs for platform adoption, data quality improvement, and analytics delivery outcomes across the trucking segment.
• Operate within agile delivery frameworks in partnership with corporate DNA engineering and platform teams as part of the Data Train.

Leadership

• Works collaboratively with others, both within the OU and with corporate departments.
• Comfortable leading and developing a team.
• Works with the senior leadership team to identify trends or processes that enhance profitability and/or reduce expenses.
• Proactively bring ideas and observations to the management team, does not wait until theories are fully confirmed.
• Works with department leaders to implement changes due to findings.

Education

• Bachelor’s Degree
• CPCU designation preferred

Required

• 8+ years of experience in data engineering, data management, or analytics leadership roles, with direct experience in insurance or financial services preferred.
• Proven experience leading data platform onboarding or migration efforts for business units or subsidiaries, including gap assessments and readiness planning.
• Strong working knowledge of modern data platforms (e.g., Databricks, Snowflake, Microsoft Fabric) and cloud-based data architectures (Azure, AWS, or GCP).
• Demonstrated ability to partner across both business and technology stakeholders — translating business requirements into data platform solutions.
• Hands-on experience with data governance programs, including data quality frameworks, metadata management, and business glossary development.
• Excellent organizational and project management skills with the ability to manage multiple concurrent workstreams across distinct operating units.
• Strong communication skills, with the ability to present complex data topics clearly to both technical teams and executive audiences.

Preferred

• Domain knowledge in commercial trucking insurance, including underwriting data, loss data, telematics, DOT compliance data, or fleet analytics.
• Experience working within a multi-operating unit or holding company structure, managing distributed data needs against a centralized platform.
• Familiarity with ETL/ELT frameworks, data modeling (e.g., medallion architecture), and data pipeline orchestration tools (e.g., dbt, Apache Airflow).
• Experience enabling AI/ML or advanced analytics use cases through data platform engineering.
• Background in data product thinking — defining reusable, governed data assets that serve multiple consumers across the segment.