5 дней назад
Actuarial Data Scientist (Insurance)
145 000 - 180 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Actuarial Data Scientist (Insurance): Building and deploying predictive loss cost models for homeowners insurance with an accent on frequency and severity modeling, pricing strategy, and production-ready Python and SQL workflows. Focus on designing by-peril models, scaling Airflow-based pipelines, validating statistical models, and translating complex actuarial insights into business recommendations.
Location: Flexible hybrid role based in the San Francisco Bay Area, Austin, Dallas, or Morristown, New Jersey; candidates may relocate to one of the U.S. hub locations with relocation assistance.
Base pay: $145,000–$160,000 in the Austin and Dallas regions; $155,000–$180,000 in the San Francisco Bay Area and New Jersey.
Company
uses technology and data to simplify homeownership and operates as a diversified carrier platform serving homeowners and insurance program partners.
What you will do
- Lead homeowners insurance modeling efforts and establish technical standards, priorities, and best practices.
- Design and build annual by-peril loss cost models for frequency and severity.
- Expand conversion, retention, demand, underwriting, and aggregation modeling to support pricing strategy and portfolio decisions.
- Implement and scale models in an Airflow-based Python pipeline with robust testing, validation, reproducibility, and maintainability.
- Develop reusable analytical tooling and workflows for the actuarial team.
- Partner with Insurance Product, Underwriting, and Engineering to deploy models and communicate business recommendations.
Requirements
- Bachelor’s degree in statistics, mathematics, data science, or another quantitative field.
- 5+ years of experience in data science, analytics, or actuarial modeling in insurance, preferably personal lines or property.
- Working knowledge of P&C insurance and loss cost modeling, including demand, underwriting, or claims modeling.
- Strong statistical modeling experience with GLMs, regularization, tree-based ensembles, and model validation techniques.
- Advanced proficiency in Python, including pandas, scikit-learn, and statsmodels, as well as SQL.
- Strong communication skills and the ability to build trust with stakeholders.
Nice to have
- ACAS or FCAS actuarial credentials.
- Master’s degree in a quantitative discipline.
- Experience with AWS, modern data platforms, and workflow orchestration tools such as Airflow.
- Experience with catastrophe modeling, geospatial analytics, or climate risk data.
Culture & Benefits
- Medical plans, employer-covered dental and vision insurance, 401(k), disability coverage, life insurance, FSAs, and an employee assistance program.
- Relocation assistance for qualified candidates moving to a hub location.
- Equity compensation eligibility, training, and internal career growth opportunities.
- Flexible time off and 12 weeks of parental leave for primary and secondary caregivers.
- Snacks, drinks, and catered lunches for onsite employees.
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