Data Project Manager

Excelerate

1d•$70 - $76

About The Position

We’re seeking a Data Project Manager who will lead data-driven initiatives that improve underwriting performance, program profitability, and operational efficiency across a portfolio of specialty insurance programs. This role partners across business, data, and technology teams to deliver scalable data solutions that support analytics, reporting, and decision-making. The Data Project Manager plays a key role in enhancing underwriting, pricing, distribution, and overall program performance through effective use of data and analytics platforms.

Requirements

5+ years of experience in data project management, analytics delivery, or data program management.
Experience working in insurance (P&C preferred) with familiarity in underwriting, claims, or actuarial data; experience within an MGA, program administrator, or specialty insurance environment is highly valued.
Strong understanding of data lifecycle concepts, including data modeling, ETL processes, data warehousing, and business intelligence.
Experience with data visualization tools (e.g., Power BI, Tableau, Looker).
Knowledge of cloud data platforms (e.g., Snowflake, Azure, AWS).
Proven ability to manage multiple cross-functional projects, complex workflows, and stakeholders in fast-paced environments.
Strong communication and stakeholder management skills, including the ability to present to executive audiences.
Proficiency in project management methodologies (Agile, Scrum, Waterfall, or hybrid).
Experience working with geographically distributed teams across multiple time zones.
Bachelor’s degree required.

Nice To Haves

PMP, Agile, or similar certification is a plus.

Responsibilities

Lead the end-to-end execution of data-focused initiatives, including data platform implementations, reporting and dashboard development, data integration, and advanced analytics use cases.
Define project scope, timelines, deliverables, and success metrics aligned with business objectives, ensuring efficient delivery and measurable outcomes.
Drive cross-functional collaboration across business stakeholders, data engineering, analytics, and IT teams to manage dependencies and deliver scalable, high-impact data solutions.
Partner with underwriting, actuarial, and program teams to deliver actionable insights that support risk selection, pricing, and program performance.
Analyze key metrics such as loss ratios, submission-to-bind conversion, retention, and overall portfolio performance.
Translate business requirements into technical data specifications and contribute to the development of data models tailored to specialty insurance lines (e.g., construction, trucking, property, hospitality).
Support the implementation and enhancement of core data infrastructure, including data warehouses, data lakes, ETL/ELT pipelines, and business intelligence tools (e.g., Power BI, Tableau).
Collaborate with engineering teams to ensure data solutions are accurate, scalable, and reliable, and facilitate integration of internal and third-party data sources (e.g., telematics, claims, and external risk data).
Own data governance and quality practices by establishing standards, definitions, and controls to ensure data integrity, consistency, and compliance with regulatory and carrier requirements.
Lead data quality initiatives, including validation, monitoring, and remediation efforts, and support the development of standardized reporting across programs and stakeholders.
Act as a key liaison between business and technical teams, translating data needs into actionable solutions through stakeholder engagement, requirements gathering, and facilitated workshops.
Provide regular updates, reporting, and executive-level summaries to communicate progress, insights, and outcomes.
Track and evaluate the performance of data initiatives against defined KPIs and business impact goals.
Identify opportunities to enhance data utilization across the insurance lifecycle and drive adoption of self-service analytics and data-driven decision-making.