Data Scientist / Senior Data Scientist

Job Opportunity:

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.

Duties & Responsibilities:

• 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.

Qualifications, Skills and Experience:

• Ph.D. or M.S. in data science, civil engineering, atmospheric science, actuarial science, computer science, mathematics, or a related field.
• 3-6 years of industry experience is preferred and required for the Senior Data Scientist level role.
• Advanced knowledge of probability theory, statistics, and machine learning methods is required.
• Practical experience in insurance, catastrophe model development, cyber and casualty risk modeling, and/or exposure data collection is preferred.
• Experience applying advanced statistical techniques and machine learning to large data sets, especially in areas of structural performance, natural catastrophe hazard, building exposure data, geospatial data, or insurance claims data.
• Familiarity with large language models (LLMs), retrieval-augmented generation (RAG), and their application in data-driven workflows is a plus.
• Strong written and verbal communication skills.
• Strong programming skills in Python (preferred), R, and SQL.
• Experience and understanding of relational and non-relational databases preferred.
• Comfort working within git-based version-control environments.
• Experience with Databricks or other cloud-based data and analytics platforms preferred.
• Highly motivated, detail oriented, and team player.

BHSI Offers:

• A competitive package and exciting growth opportunities for career-oriented teammates.
• A dynamic, action oriented, and thoughtful environment centered on always doing the right thing for our customers, teammates, and our other stakeholders.
• A purposely non-bureaucratic organization that embraces simplicity over complexity and emphasizes individual excellence in a team framework.
• Benefits that support your life and well-being, which include: Comprehensive Health, Dental and Vision benefits. Disability Insurance (both short-term and long-term). Life Insurance (for you and your family). Accidental Death & Dismemberment Insurance (for you and your family). Flexible Spending Accounts. Health Reimbursement Account. Employee Assistance Program. Retirement Savings 401(k) Plan with Company Match. Generous holiday and Paid Time Off. Tuition Reimbursement. Paid Parental Leave.

The base salary range for this position in Atlanta, GA, Boston, MA, or San Ramon, CA is $100,000 to $160,000, along with annual bonus eligibility. Total compensation for a candidate is determined by their relevant skills, location, and experience. We value our teammates – both their capabilities and character – as demonstrated by our amazing culture.