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Tier-1 brand, popular Data Scientist title, broad skills and likely metro location increase competitive density.
Core data science skills are transferable, but casualty pricing domain knowledge increases role-specific bias.
Mandatory Python, SQL, Power BI and modelling skills plus degree expectations create moderate candidate filtering.
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Develop and maintain complex casualty analytics models, data pipelines, and automation tools supporting brokers in liability risk pricing.
Transform, cleanse, and analyze complex claims and exposure data to provide actionable insights and improve casualty pricing processes.
Collaborate with brokers and stakeholders to create dashboards and decision-support tools, ensuring efficient and scalable analytical workflows.
Strong proficiency in Python, SQL, Power BI, and Excel for data processing, automation, and visualization.
Degree in a quantitative or technical field such as statistics, mathematics, engineering, data science, or computer science.
Experience in data science, analytics, modeling or automation-focused roles; insurance experience preferred but not mandatory.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building automated workflows and analytical tools to handle large, complex datasets in a business environment focused on casualty analytics.
Capable of translating technical outputs into commercial terms and collaborating with business stakeholders (brokers, underwriters).
Interested in growing expertise in liability risk pricing and improving data-driven decision-making in casualty insurance analytics.