Data Scientist (Hybrid - Plymouth Meeting Area, PA)Our client is seeking a Data Scientist to collaborate with teams across underwriting, product, operations, and executive leadership. This role is responsible for tackling business challenges from start to finish, combining analytical rigor with practical application. The ideal candidate thrives working independently while maintaining strong cross-functional partnerships. This position follows a hybrid schedule in the greater Plymouth Meeting, PA area.Key ResponsibilitiesUnderwriting & Risk Insights
- Evaluate submission, quotation, and binding data to uncover patterns related to conversion rates, declines, and alignment with underwriting strategy.
- Assist in pricing evaluations and rate adequacy analyses alongside actuarial teams or external partners, leveraging normalized loss and exposure data.
Product & Growth Analytics
- Work closely with product and distribution teams to design and enhance funnel metrics, conversion tracking, and cohort-based reporting.
- Build and maintain models focused on customer lifetime value (LTV) and retention, helping identify policies at risk of non-renewal.
- Assess distribution channel performance to highlight expansion opportunities, cross-selling strategies, and optimal resource allocation.
Data Architecture & Engineering Support
- Partner with engineering and IT functions to develop and sustain data pipelines integrating multiple sources such as policy administration systems, claims data, and third-party providers (e.g., LexisNexis, Verisk, CoreLogic).
- Maintain strong standards for data quality, governance, and documentation across analytical assets.
- Contribute to evolving a scalable analytics environment, including data warehouse structures and business intelligence tool integration.
Reporting & Communication
- Build and manage dashboards and reporting tools that provide clear visibility into key metrics for underwriting, operations, and leadership teams.
- Present analytical insights in a clear, business-friendly manner to both technical and non-technical audiences.
- Produce periodic reports for external stakeholders, including carrier and capacity partners, ensuring consistency and accuracy.
- Enable self-service analytics through modern BI platforms and reporting solutions.
Qualifications- Minimum of 3 years of experience in analytics, data science, or a related quantitative field; background in property & casualty insurance is strongly preferred.
- Bachelor's degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Actuarial Science, or Economics (advanced degrees are a plus).
- Proficiency in Python and/or R for data analysis and model development.
- Advanced experience with SQL and working across large, complex datasets from multiple systems.
- Track record of developing and deploying predictive models in production environments, including documentation and stakeholder enablement.
- Solid understanding of P&C insurance fundamentals (e.g., premium, loss ratio, combined ratio, policy lifecycle).
Preferred Background- Experience within a P&C carrier, MGA, program administrator, broker, or insurtech organization, particularly in data-focused roles. Familiarity with MGA-specific data structures (e.g., bordereaux reporting, policy systems, and partner data requirements) is highly beneficial.
- Exposure to building and implementing AI/ML-driven features within insurance products, including applications such as document automation, underwriting support tools, or large language model (LLM) integrations.
