Data Scientist
About The Position
SageSure, a leader in catastrophe-exposed property insurance, is seeking a Data Scientist to join their team. This role involves combining geospatial analytics, statistical modeling, machine learning, and software development to address complex underwriting and risk management challenges. The Data Scientist will develop scalable analytical tools, utilize spatial, property, policy, and claims data, automate complex workflows, and collaborate with cross-functional teams including Product Development, Underwriting, Cat Modeling, Data, and Risk Management to support profitable growth. The ideal candidate is passionate about solving business problems with data science, comfortable with large and complex datasets, and experienced in applying modern analytics and AI techniques.
Requirements
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Geographic Information Systems (GIS), Engineering, Information Science, or a related quantitative discipline.
- 5 to 7 years of experience in data science, analytics, software development, or geospatial analytics.
- Experience with statistical modeling techniques and building predictive models using Python, SAS or R, and strong statistical modeling techniques.
- Experience developing solutions using SQL and relational databases.
- Experience working with large structured and unstructured datasets.
- Experience using GIS platforms such as ESRI ArcGIS, ArcGIS Pro, ArcObjects, or equivalent geospatial technologies.
- Experience developing automated data processing and analytical workflows.
- Experience building software applications or analytical tools that support business operations.
- Strong problem-solving and communication skills.
Nice To Haves
- Experience in Property & Casualty insurance.
- Familiarity with catastrophe models and exposure management.
- Experience with geospatial statistics and spatial modeling.
- Experience with AI and Generative AI technologies.
- Experience with C#, .NET, or software engineering principles.
Responsibilities
- Deliver analytical insights that support business decisions as a member of a cross-functional team — including Product Development, Underwriting, Cat Modeling, Data and Risk Management.
- Design and develop statistical, geospatial, and machine learning models that improve underwriting performance and portfolio management.
- Analyze spatial, exposure, catastrophe, and loss data to identify trends, concentrations of risk, and business opportunities.
- Execute predictive analytics, machine learning, and AI models that support pricing, underwriting, and operational efficiency.
- Apply statistical techniques including regression, clustering, classification, time series analysis, and causal inference to solve business problems.
- Support building software applications and analytical tools that automate underwriting and risk analysis.
- Build reusable data pipelines and automate data collection, cleansing, transformation, to support underwriting, product development and risk management.
- Design and maintain geospatial datasets using internal and third-party data sources.
- Develop software applications and APIs that support underwriting analytics and business decision making.
- Mentor junior team members and promote best practices for AI use within the department.
- Perform other duties and special projects as assigned.
Benefits
- Named among the Best Places to Work in Insurance by Business Insurance for four years in a row (2020-2023)
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
