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About the role

Senior P&C Actuarial Data Science Role Actuarial data-science crossover Closer to a data-science crossover than a conventional modelling IC—the models must be deployed in production workflows and scaled across the team. Senior P&C actuarial data science role in the San Francisco Bay Area, focused on homeowners pricing and predictive modeling. You'll own frequency, severity, demand, retention, and aggregation models, then deploy them through Python and SQL workflows. The role reports to the Director, Actuarial and is flexible/hybrid, with other hubs in Texas and New Jersey.
Requirements
Must have:
  • Bachelor's degree in statistics, mathematics, data science, or other quantitative field 5+ years of experience in data science, analytics, or actuarial modeling in insurance
  • Working knowledge of P&C insurance in loss cost modeling
  • Exposure to demand, underwriting, and/or claims modeling
  • Strong background in statistical modeling: GLMs, regularization, tree-based ensembles (XGBoost, LightGBM), and model validation
  • Knowledge of actuarial principles as they relate to insurance pricing
  • Advanced proficiency in Python (pandas, scikit-learn, statsmodels) and SQLExcellent communication skills and ability to build trust with stakeholders at all levels
  • Strongly preferred: Personal lines or property insurance experience
Nice to have:
  • Advanced degree (Master's) in quantitative discipline
  • Actuarial credentials - ACAS/FCASExperience with modern data platforms, cloud infrastructure (AWS), and workflow orchestration (Airflow)
  • Experience with catastrophe modeling, geospatial modeling, or climate analytics data
  • Tools Power_BI Tableau Excel Domain Homeowners Personal_Lines

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