Vice President, Data and Analytics

About the role

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.

Responsibilities

• 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.
• Cook up and manage onboarding playbooks and project plans tailored to data landscape, technical readiness, and business priorities.
• Cook up 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 brings 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.

Qualifications

• Education

• Bachelor’s Degree
• CPCU designation preferred

• Required Experience

• 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 Experience

• 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.