Director, General Liability Pricing Analytics - REMOTE

Director, General Liability Pricing Analytics The Role

In this position, you will work at the intersection of predictive analytics, actuarial thinking, and pricing strategy. You will partner closely with teammates and business partners to build, enhance, and refine models that support general liability insurance pricing. You will also have the opportunity to work across a variety of projects, expand your technical toolkit, and deepen your understanding of how modeling drives real business outcomes.

As Director, General Liability Pricing Analytics, you will serve as the senior technical leader for General Liability pricing data science and price modeling. You will lead the development, enhancement and implementation of pricing models and data science solutions that support profitable growth, competitive market position and sound underwriting decisions.

This is a hands-on people leadership role with direct reports. You will combine deep expertise in actuarial, statistical and predictive modeling with the ability to translate complex analysis into clear recommendations for Actuaries, Underwriting, Product, Claims, Finance and senior business leaders. You will guide and develop analytical professionals, including direct reports, lead complex work across functions and help establish consistent standards for model quality, documentation, validation and use.

• Set technical direction for General Liability pricing strategy, segmentation, rating analysis, portfolio insights and model delivery.
• Lead the research, development, implementation and monitoring of advanced statistical, actuarial, predictive and risk models.
• Explore and pilot emerging AI tools and advanced statistical methods to improve General Liability price modeling and analytical workflows, while maintaining appropriate standards for governance, validation, explainability and production readiness.
• Evaluate data, assumptions, methodologies and model outputs; identify limitations or unreasonable results and recommend corrective actions.
• Own model governance standards covering validation, documentation, reproducibility, implementation readiness and business continuity.

• Translate underwriting and business needs into clear analytical questions, recommendations and delivery plans.
• Partner with Actuaries, Underwriting, Product, Claims, Finance, Data, Analytics, and Technology teams to ensure analytical solutions are understood and applied effectively.
• Convert complex findings into concise recommendations and decision materials for technical, non-technical and senior leadership audiences.
• Advise on products, data needs, rating approaches, implementation implications and opportunities to improve profitability and underwriting decisions.

• Lead complex projects, cross-functional reviews and working sessions that align stakeholders around priorities, tradeoffs and actions.
• Manage scope, timelines, resources and delivery quality across assigned work.
• Identify opportunities to improve data quality, analytical processes, technology enablement and model delivery practices.
• Represent Nationwide in governance forums and with auditors, regulators, vendors or industry groups, as appropriate.

• Coach and develop analytical talent through technical guidance, peer review, training, career development and feedback.
• Lead the day-to-day people management of direct reports, including hiring, performance management, talent planning, resource alignment and career development.
• Perform other responsibilities as assigned.

• Typically, seven or more years of experience in actuarial, statistical, predictive modeling, risk analytics, pricing analytics or a related quantitative discipline.
• Experience leading complex projects, setting analytical direction and delivering results across business functions.
• Graduate or PhD degree in actuarial science, statistics, mathematics, data science, economics, finance, engineering or a related quantitative field; graduate study preferred.

• Experience developing, validating, implementing or monitoring complex models used to support business decisions.
• Strong understanding of statistical inference, predictive modeling, model diagnostics, data quality, assumptions and model limitations.
• Working knowledge of commercial property and casualty insurance;
  General Liability pricing, underwriting or portfolio experience strongly…