Data Scientist​/Senior Data Scientist; Risk Modeling

Atlanta, GA, US

7 days ago Requisition

Salary Range: $ To $ Annually

A strategic and trusted insurance partner, Berkshire Hathaway Specialty Insurance (BHSI), provides a broad range of commercial property, casualty and specialty insurance coverages and outstanding service to customers and brokers around the world. Part of Berkshire Hathaway’s insurance operations, we bring our solutions to market with our stellar brand name, top-rated balance sheet, and the expertise of our global team of professionals, who exude excellent capabilities and strong character.

We are a values-based organization where respect, integrity, excellence, collaboration, and passion define who we are and how we do business. We value diversity of backgrounds, experience, and perspectives and strive to foster an inclusive environment that enables all our team members to bring their best selves to work. We are one team committed to building a culture where every teammate has the opportunity to contribute and be recognized.

Want to be part of the team building the finest property, casualty and specialty lines insurance company in the world?

Berkshire Hathaway Specialty Insurance (BHSI) has an exciting opportunity for Data Scientist / Senior Data Scientist to join the Catastrophe Engineering and Analytics (CAT E&A) team. CAT E&A is an innovative and versatile technical team conducting catastrophe risk research and development and providing complex quantitative metrics that inform underwriting decisions across multiple lines of business.

The successful candidate will be responsible for identifying and applying cutting-edge data science techniques to build a better view of the risk for multiple perils. You will work across functional areas and perils within the team, supporting the development of models for various natural catastrophes, natural hazards, building vulnerability, and man-made risks such as cyber, casualty, among others. In addition, you will conduct in-depth evaluation of vendor models, research and develop internal views of exposure and risks, consult on account-specific risk analyses, and develop internal tools to facilitate account underwriting decision-making and other related activities.

• Evaluate and develop insights into large and diverse data sets from claims, hazard models, structural analysis, geospatial sources, and various other public/proprietary datasets.
• Develop and maintain expertise in advanced data science, machine learning, and artificial intelligence techniques, and their application to understanding risk.
• Work with domain experts across teams and perils to enhance our use of available data.
• Propose and execute innovative solutions to insurance problems that directly impact BHSI underwriting decisions.

Educational Background

• Advanced degree (Master's or Ph.D.) in Statistics, Actuarial Science, Applied Mathematics, Data Science, Engineering, or other equivalent quantitative discipline.
• Strong academic foundation in probability theory, statistical inference, stochastic processes, and Bayesian statistics.

Technical & Analytical Skills

• Deep expertise in probability models commonly used in insurance (e.g., frequency-severity models, GLMs, loss distributions).
• Predictive analytics
• Pricing & underwriting analytics
• Catastrophe exposure analysis
• Proficiency in statistical and machine learning techniques, including:
  • Regression (GLM, GAM, GAMMs)
  • Time-series forecasting
  • Gradient boosting, random forests, and other tree-based models, neural networks models
  • Clustering and segmentation
  • Bayesian methods
• Hands-on experience with key programming tools:
  • Python (Num Py, pandas, scikit-learn; PyTorch/Tensor Flow a plus)
  • R (actuarial/statistical packages)
  • SQL for data extraction and manipulation
  • Familiarity with Git and Docker is a plus
• Experience with big data and distributed computing (e.g., Spark, Databricks, AWS/GCP/Azure) is a plus.

Preferred Domain Knowledge in Risk Modeling

• Strong understanding of property & casualty insurance, including:
  • Exposure modeling
  • Loss distributions (e.g., Pareto, lognormal, gamma)
  • Catastrophe risk concepts and tail modeling
  • Portfolio risk…