• Lead the team responsible for building the trusted data foundation that powers decision-making across the company. • Oversee a team of analytics engineers who transform raw data into scalable, reliable, and well-governed data models. • Partner closely with Engineering, Product, Data Science, Finance, Marketing, Sales, Customer Success, and Executive Leadership to define our data strategy. • Balance technical excellence with business impact, helping the organization become increasingly data-driven while building a high-performing and inclusive team.

Title: Reinsurance Analytics Developer Location: United States Job Description: ' Make a difference with a career in insurance At The Cincinnati Insurance Companies, we put people first and apply the Golden Rule to our daily operations. To put this into action, we’re looking for extraordinary people to join our talented team. Our service-oriented, ethical, knowledgeable, caring associates are the heart of our vision. If you’re ready to build productive relationships, collaborate within a diverse team, embrace challenges and develop your skills, then Cincinnati may be the place for you. We offer career opportunities where you can contribute and grow. Build your future with us Cincinnati Re is seeking a talented Reinsurance Analytics Developer to enhance rating tools, data analytics, and reporting. This role focuses on refining reinsurance pricing models, streamlining actuarial processes, and collaborating across teams to support data-driven underwriting decisions. Starting Pay: The pay range for this position is $125,000 - $225,000 annually. Pay is based on the applicant’s education, experience, knowledge, skills and abilities. Eligible associates may also receive an annual cash bonus and stock incentives based on company and individual performance. Be ready to: - develop, test, and maintain actuarial models, pricing tools, and underwriting templates - convert Excel based actuarial tools into software solutions utilizing Python, R, SQL, or similar technologies - utilize version control (e.g., Git) and follow best practices for code documentation, testing, and deployment - enhance automation of pricing workflows to improve efficiency and accuracy - explore and implement AI-assisted solutions to improve data ingestion, exposure processing, pricing workflow efficiency, and analytical insights - build and maintain data pipelines to support seamless data processing and reporting - conduct ad-hoc research and technical analysis to assist pricing actuaries - collaborate with catastrophe modeling, portfolio management, and underwriting teams to support reinsurance analytics strategies - stay up to date with industry trends, emerging technologies, and best practices in modeling and reinsurance - occasional travel for internal meetings (about 8 trips a year) Be equipped with: Required: - 5+ years of experience in actuarial, reinsurance, or insurance analytics - proficiency in programming languages such as Python, R, SQL, or similar - experience developing or enhancing analytical tools, data workflows, or software solutions - strong problem-solving skills with the ability to work with complex and unstructured datasets - effective communication skills, with the ability to explain technical concepts to both technical and non-technical stakeholders - ability to work both independently and collaboratively in a fast-paced, project-driven environment Preferred: - experience in P&C reinsurance pricing and underwriting workflows - experience with data pipelines, databases, or data platforms (e.g., SQL Server, PostgreSQL, Snowflake) - knowledge of catastrophe modeling, portfolio management, or financial reporting Bring education and experience from: - Bachelor’s degree in Actuarial Science, Data Science, Computer Science, Mathematics, or a related field - progress toward or attainment of actuarial credentials (ACAS, FCAS, or equivalent), or comparable experience preferred Enhance your talents Providing outstanding service and developing strong relationships with our independent agents are hallmarks of our company. Whether you have experience from another carrier or you’re new to the insurance industry, we promote a lifelong learning approach. Cincinnati provides you with the tools and training to be successful and to become a trusted, respected insurance professional – all while enjoying a meaningful career. Enjoy benefits and amenities Your commitment to providing strong service, sharing best practices and creating solutions that impact lives is appreciated. To increase the well-being and satisfaction of our associates, we offer a variety of benefits and amenities. Embrace a diverse team As a relationship-based organization, we welcome and value a diverse workforce. We grant equal employment opportunity to all qualified persons without regard to race; creed; color; sex, including sexual orientation, gender identity and transgender status; religion; national origin; age; disability; military service; veteran status; pregnancy; AIDS/HIV or genetic information; or any other basis prohibited by law. All job applicants have rights under Federal Employment Laws. Please review this information to learn more about those rights.

• Build and optimize data pipelines and analytical tools for scale • Collaborate with both technical and non-technical areas of the business • Contribute to core data assets for equitable book of business assignments • Build and maintain semantic models for analytics and AI consumption • Build out scalable data models for the HubSpot business • Expand suite of dbt patterns and macros • Support data observability and pipeline reliability • Build analytical applications in Hex • Gather requirements with internal stakeholders • Document data pipelines, processes, and best practices • Contribute to shared analytics best practices across HubSpot’s broader data community

• Build and scale data pipelines for product events, usage data, and customer datasets • Develop analytics infrastructure using technologies like Kafka, ClickHouse, and PostgreSQL • Own data models, KPI definitions, and metric layers powering dashboards and product features • Build reliable ingestion processes for both structured and messy customer-provided datasets • Ensure privacy-first data practices through anonymisation, pseudonymisation, and tenant-level controls • Collaborate with engineering and product teams to make data accessible, trusted, and actionable