Salary: $145k - $180k
Experience: 5+ Years

Role Summary

Role type

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 SQL
Excellent 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/FCAS
Experience with modern data platforms, cloud infrastructure (AWS), and workflow orchestration (Airflow)
Experience with catastrophe modeling, geospatial modeling, or climate analytics data

Skills & Domain

ToolsPower_BITableauExcel

DomainHomeownersPersonal_Lines

Role Summary

Role type

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.

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 SQL
Excellent 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/FCAS
Experience with modern data platforms, cloud infrastructure (AWS), and workflow orchestration (Airflow)
Experience with catastrophe modeling, geospatial modeling, or climate analytics data

Skills & Domain

ToolsPower_BITableauExcel

DomainHomeownersPersonal_Lines

Role Summary

Role type

Requirements

Must have

Strongly preferred

Nice to have

Skills & Domain

Role Summary

Role type

Requirements

Must have

Strongly preferred

Nice to have

Skills & Domain

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