Actuarial Data Science Lead
Core
Own end-to-end development of commercial auto pricing models and loss cost models to set pricing for Shepherd's commercial auto book.
Role type
Lead, actuarial data science (pricing models)
Builds
Production pricing and loss cost models for commercial auto insurance
Domain
Commercial insurance / Actuarial science / Predictive analytics
Deliverable
production ML models
Required skills
Commercial auto pricing model development, loss cost modeling, feature engineering for small/messy data, GLMs, GBDTs, time series analysis, heavy tail distributions, Bayesian methods, Python, SQL, ACAS/FCAS designation, model monitoring, experiment design and back-testing
Preferred skills
Insurance/insurtech/fintech domain experience, telematics pricing, NLP/document extraction, AWS model deployment infrastructure
Technologies
Python, SQL, AWS
Responsibilities
Develop and deploy predictive models for loss ratios and pricing accuracy, design feature pipelines transforming raw data into model inputs, collaborate with actuaries and underwriters to validate outputs, build model monitoring frameworks for drift and performance tracking, run experiments to quantify model impact on portfolio quality
Seniority
Senior, hands-on IC with project management