The individual in this role will collaborate with underwriting, product, operations, and leadership teams to manage projects from inception to completion. Responsibilities include building and maintaining data pipelines by integrating information from policy administration systems, claims platforms, and third-party providers. The role involves analyzing submission, bind, and quote data to determine trends in hit ratios and declination patterns. Furthermore, the professional will support pricing analysis and adequacy reviews in conjunction with actuarial resources. The position also requires the development of customer lifetime value and retention models to inform renewal strategies. Finally, the individual will evaluate distribution partner performance to identify growth opportunities and capacity allocation priorities.

Candidates must possess at least three years of experience in data science, analytics, or quantitative research, with a preference for background in the property and casualty insurance sector. A bachelor’s degree in a quantitative discipline such as statistics, mathematics, computer science, actuarial science, or economics is required, while a master’s degree is considered an asset. Proficiency in Python or R is necessary for statistical analysis and model development. Additionally, the role requires advanced SQL skills for managing complex relational datasets and practical experience in deploying predictive models. A working knowledge of core insurance concepts, including premium, loss ratio, and policy lifecycle, is also essential.