Data Scientist

SageSure

$110K — $130K *
Finance & Insurance
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, GIS, Engineering, or related field.
  • 5-7 years of experience in data science, analytics, software development, or geospatial analytics.
  • Proficient in statistical modeling techniques and predictive modeling using Python, SAS, or R.
  • Skilled in SQL and relational databases for data management.
  • Experience handling large structured and unstructured datasets.
  • Familiar with GIS platforms like ESRI ArcGIS or similar technologies.
  • Background in developing automated data processing and analytical workflows.

Responsibilities

  • Deliver analytical insights that inform business decisions within a cross-functional team.
  • Design and develop statistical, geospatial, and machine learning models to enhance underwriting performance.
  • Analyze catastrophe and loss data to spot trends and risk concentrations.
  • Execute predictive analytics and AI models to improve pricing and operational efficiency.
  • Apply statistical techniques to solve complex business challenges.
  • Support building software applications and analytical tools for underwriting and risk analysis.
  • Mentor junior team members and advocate for best practices in AI.

Benefits

  • Opportunity to join a stable and growing company with a startup atmosphere.
  • Collaborative work environment with cross-functional teams.
  • Engagement with innovative data science and machine learning projects.
  • Mentorship opportunities within the team.
  • Possibility of working on impactful projects in catastrophe-exposed property insurance.
Full Job Description
Overview:

If you're looking for the stability of a profitable, growing company with the entrepreneurial spirit of a startup, we're hiring. SageSure, a leader in catastrophe-exposed property insurance, is seeking a Data Scientist to join our team. In this role, you will combine geospatial analytics, statistical modeling, machine learning, and software development to solve complex underwriting and risk management challenges.

You will develop scalable analytical tools, leverage spatial, property, policy and claims data, automate complex workflows, and work within a cross-functional team - including Product Development, Underwriting, Cat Modeling, Data and Risk Management - to support profitable growth.

The ideal candidate enjoys solving difficult business problems through data science, thrives working with large and complex datasets, and has experience applying technologies alongside modern analytics and AI techniques.

What you'd be doing:
  • 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

We are looking for someone who has:
  • 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

Highly preferred candidates also have:
  • 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.


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