Analytics & Modeling Analyst

Skills and Competencies

• 3 to 5 years of experience in data analytics, statistical analysis, analytical research, spatial data analysis, or related quantitative disciplines, with strong proficiency in SQL and Python
• Hands-on experience using Python libraries such as Pandas and NumPy to analyze, validate, transform, and interpret large datasets Strong analytical, critical thinking, and problem-solving skills, with the ability to translate business requirements into actionable insights and communicate findings to diverse stakeholders
• Experience with data quality assessment, testing, reconciliation, automation, and process improvement initiatives; familiarity with AI-assisted workflows and effective prompting techniques
• Exposure to visualization tools such as Tableau or Power BI, cloud-based analytical environments, data pipelines, or ETL workflows is preferred
• Knowledge of GIS, catastrophe modeling, insurance analytics, risk management, machine learning, or related analytical domains is advantageous

Education

Responsibilities

• Analyze structured, semi-structured, and geospatial datasets to uncover trends, identify anomalies, and generate insights that support business and modeling decisions
• Support the development and enhancement of property insurance datasets, analytical products, spatial data layers, and reporting solutions
• Apply statistical and analytical techniques to improve data quality, validate datasets, investigate issues, and contribute to model and product improvement initiatives