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. 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.