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.
Key Responsibilities
Technical and Model Leadership
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.
Business Partnership and Decision Support
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.
Delivery and Continuous Improvement
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.
Talent and Team Leadership
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.
Required Qualifications
Education and Experience
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.
Technical Expertise
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 preferred.
Proficiency in Python and GitHub-based version control, along with experience using cloud-based analytics, model development, or deployment platforms such as Databricks, SageMaker, or comparable tools.
Demonstrated experience taking a model from development through production deployment, testing, documentation, monitoring, and post-deployment validation.
Leadership and Professional Effectiveness
Sound judgment in ambiguous business situations, with the ability to develop practical, well-supported recommendations.
Ability to communicate sophisticated technical concepts in clear business language and influence technical and non-technical partners.
Demonstrated commitment to Nationwide Values and Guiding Behaviors.
Preferred Qualifications
Insurance and Actuarial Depth
Associate or Fellow of the Casualty Actuarial Society, or meaningful progress toward an actuarial designation.
Experience with commercial insurance pricing, loss-cost analysis, frequency and severity modeling, segmentation, indication analysis, rate implementation or portfolio monitoring.
Advanced Modeling and Governance
Experience applying machine learning, generalized linear models, credibility methods, stochastic techniques or other advanced quantitative methods to insurance problems.
Experience with model governance, peer review, independent validation, regulatory support or audit response.
Business Impact and People Leadership
Experience translating model output into underwriting actions, pricing recommendations and measurable business outcomes.
Experience directly managing and developing actuaries, data scientists, analytic scientists or pricing professionals.
Leadership Profile
The successful candidate will be a technically credible, business-oriented leader who:
Brings curiosity, rigor and sound judgment to complex pricing and risk questions.
Connects analytical work to underwriting decisions, customer outcomes, profitability and enterprise strategy.
Creates clarity when objectives, data or stakeholder perspectives are competing or incomplete.
Raises the quality of analytical work through thoughtful challenge, peer review and disciplined documentation.
Develops people while maintaining high standards for accountability, collaboration and delivery.
Builds durable partnerships and communicates with confidence at all levels of the organization.
Job Conditions
This role can be staffed fully remote.
#LI-remote
#LI-SM1
Job Description Summary
Do you have the desire to play a critical role in driving data-based business outcomes? At Nationwide, our Analytic Scientists are responsible for modeling complex problems, discovering insights and identifying business opportunities using scientific research methods, statistics, machine learning, and data visualization techniques. They participate in all phases of the analytic lifecycle, from research design, data collection and data processing to model building, deployment, and presentation of results. We value a dedication to lifelong learning and strong quantitative judgment. If you are a methodological generalist who is adept at applying your technical skill set to a wide range of business applications, we want to know more about you!
As a Director, you’ll lead a team of Analytic Scientists and work directly with business partners to define project scope and build solutions. We’ll count on you to structure and lead large, complex analyses across one or more business areas and effectively synthesize analytic results to improve business outcomes. You’ll build lasting business relationships across and help business leaders navigate complex, competing objectives. You’ll be a subject matter authority, in both analytical and business applications, and will communicate effectively with technical and non-technical audiences. Your proficiency with advanced statistical and machine learning techniques will help you direct the application of these techniques to solve complex problems.
Job Description
Key Responsibilities
Leads a team that works on a wide array of statistical and machine learning projects across the enterprise.
Collaborates with business partners to build consensus around problems of broad scope and business impact. Guides the research, analysis, implementation and monitoring of modeling methodology to solve those problems.
Upholds a high standard for methodological rigor, sound statistical inference and robust model validation.
Plans and manages the execution of analytic work including defining project scope, schedule, resource requirements and delivery timelines.
Collaborates with multiple departments or business functions to accomplish management goals, objectives and tasks.
Communicates technical work to leadership.
Demonstrates knowledge of a wide array of business practices and business knowledge. Applies knowledge to direct projects that provide creative solutions to complex business problems.
Directs associate management, including performance management, salary planning and administration, training and development, workflow and organizational planning, hiring and placement, and disciplinary actions.
May perform other responsibilities as assigned.
Reporting Relationships: Reports to Associate Vice President, Vice President. Manages a team of 4 or more associates responsible for creating a high-performance, business-focused team. Ensures that team members at all levels are supported with career development, succession planning, performance management, etc.
Typical Skills and Experiences:
Education: Preferred undergraduate or graduate studies in statistics, engineering, math, quantitative social science fields, or related areas. Experience building and deploying machine learning and/or statistical models or executing quantitative research studies may be considered in lieu of formal education.
Experience: Typically, 10 or more years of related work experience in a relevant field.
Knowledge, Abilities and Skills:
Quantitative judgment: Demonstrated knowledge of building and deploying machine learning and/or statistical models.
Research methods: Knowledge of multiple quantitative research and analysis approaches and their tradeoffs.
Strong project management skills and the ability to handle multiple large projects simultaneously.
Advanced written and verbal communication skills. Ability to communicate technical concepts to all levels of leaders and associates.
Seeks and objectively considers input from appropriate sources. Considers implications of actions on other areas, people, and processes when making decisions.
Drives decisions, projects, and processes without formal authority. Works directly with a variety of people to create broad acceptance for proposed innovations and changes.
Implements changes which improve business processes. Anticipates and responds to changing situations, needs and expectations.
Able to handle large and complex engagements focused on broader business activities.
Ability to lead key relationships and act independently.
Programming ability: Python, R, SQL, or any other transferrable language (MATLAB, Java, etc.).
Passion, inquisitiveness, creativity, self-starters and team builders.
Other criteria, including leadership skills, competencies and experiences may take precedence.
Staffing exceptions to the above must be approved by the Vice President and HR Vice President.
Values: Regularly and consistently demonstrates the Nationwide Values.
Job Conditions:
Overtime Eligibility: Exempt (Not Eligible)
Working Conditions: Normal office environment
