Liberty Mutual’s U.S. Retail Markets organization is seeking a Senior Director II, Data Science to lead the USRM Data Science Complex Components team. This executive-level role is responsible for advancing the science, delivery, and business impact of several of the most important modeling components that support pricing, underwriting, and product management across the U.S. Retail Markets portfolio.

The Complex Components team is composed of approximately three dozen data scientists and data science managers organized across three core domains: high-cardinality variables, such as territory, small business class, and vehicle specifications; telematics; and credit-based models. These teams develop, enhance, and deploy sophisticated modeling approaches that help Liberty Mutual better understand risk, improve pricing precision, support underwriting effectiveness, and enable competitive go-to-market strategies.

This leader will serve as a critical bridge between advanced research and near-term business execution. They will connect the work of a technically deep, research-oriented data science organization to the practical needs of pricing, product, underwriting, and go-to-market teams. Success requires strong technical judgment, exceptional leadership capability, and the ability to navigate a highly matrixed environment with clarity, influence, and enterprise perspective.

Key Responsibilities:

• Lead and develop a multi-team data science organization responsible for complex modeling components supporting USRM pricing and underwriting.
• Set the strategic direction for data science research and model advancement across high-cardinality variables, telematics, and credit models.
• Partner closely with Product Design & Modeling, Product Management, Underwriting, Analytics, Technology, and operational stakeholders to ensure data science work is aligned to business priorities and translated into measurable outcomes.
• Oversee the development, validation, implementation, and ongoing enhancement of pricing and underwriting model components.
• Balance longer-term scientific advancement with near-term tactical delivery, including support for ongoing pricing model rollouts and business implementation needs.
• Build strong connections between technical research teams and business-facing partners, ensuring that model innovations are actionable, explainable, and adopted effectively.
• Develop data science managers and senior individual contributors through coaching, career development, performance management, and thoughtful organizational design.
• Create an environment that promotes scientific rigor, innovation, collaboration, accountability, and sound judgment.
• Influence senior leaders across the organization by clearly communicating technical concepts, tradeoffs, risks, and recommendations in business-relevant terms.
• Help establish priorities, manage capacity, and guide investment decisions across a broad and technically complex portfolio of modeling work.
• Ensure appropriate model governance, documentation, monitoring, and risk management practices are embedded in the team’s work.

• Competencies typically acquired through an advanced degree (in Statistics, Mathematics, Data Science or other relevant field of study) or Actuarial designation and 8+ years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) with 10+ years of relevant experience.
• Significant experience leading data science, analytics, actuarial, modeling, or quantitative research teams in a complex business environment.
• Demonstrated ability to lead leaders and manage a department-scale organization, including data scientists and data science managers.
• Strong understanding of predictive modeling, machine learning, statistical methods, and model implementation in business decision-making contexts.
• Experience supporting pricing, underwriting, product management, insurance, financial services, or another analytically intensive business domain is strongly preferred.
• Proven ability to connect advanced technical research to practical business execution and near-term operational needs.
• Experience working in matrixed organizations and influencing outcomes across teams without relying solely on direct authority.
• Strong executive communication skills, including the ability to translate complex technical work into clear implications for business leaders.
• Track record of developing talent, building high-performing teams, and creating inclusive environments where technical professionals can grow.
• Ability to balance scientific rigor, regulatory and governance expectations, implementation feasibility, and business urgency.
• Strategic mindset with strong judgment, prioritization skills, and enterprise orientation.

What Success Looks Like

The successful candidate will be a senior data science leader who can elevate the technical sophistication of Liberty Mutual’s complex modeling components while ensuring the work remains tightly connected to business value. They will help their teams advance the science of pricing and underwriting models, support successful deployment of those models, and strengthen the partnership between research-oriented data science teams and the business stakeholders who depend on their work.

They will be equally comfortable discussing modeling tradeoffs with technical experts, aligning priorities with business leaders, developing data science managers, and helping teams navigate ambiguity in a large, matrixed organization.