VP, Underwriting Analytics & Portfolio Insights

Guy Carpenter; Denver (CO); Hybrid; USD 105,000 - 193,000; Full time

Job summary

Guy Carpenter's Underwriting Analytics team seeks a skilled data scientist to develop models and analytical tools that support underwriting strategy, portfolio insights, risk segmentation, and decision making.

You will collaborate with underwriting, broking, actuarial, catastrophe modeling, and portfolio teams to translate business questions into scalable solutions, build features from insurance datasets, and communicate results to technical and non-technical stakeholders.

Qualifications

• Bachelor's degree in a quantitative field.
• 3–6 years of data science/analytics experience.
• Prior insurance industry experience.
• Strong programming in Python and SQL; familiarity with R is a plus.
• Experience building predictive/diagnostic models.
• Solid grounding in probability and statistics.

Responsibilities

• Develop and enhance analytical models, decision tools, and data products.
• Apply statistical and ML techniques to large datasets to identify insights.
• Collaborate with underwriting, broking, actuarial, catastrophe modeling, and portfolio teams.
• Build models and frameworks for risk segmentation, portfolio monitoring, and underwriting optimization.
• Design exploratory data analyses to assess portfolio characteristics and trends.
• Engineer features from structured and semi-structured insurance data sources.
• Support productionization of analytical workflows, including validation and monitoring.
• Create clear visualizations and presentations for technical and non-technical stakeholders.

Skills

Python

SQL

Data science

Statistics

Machine learning

Education

Bachelor's degree in Data Science or related field

Tools

R

Pandas

Job description

Guy Carpenter's Underwriting Analytics team seeks a skilled data scientist to develop models and analytical tools that support underwriting strategy, portfolio insights, risk segmentation, and decision making.

You will collaborate with underwriting, broking, actuarial, catastrophe modeling, and portfolio teams to translate business questions into scalable solutions, build features from insurance datasets, and communicate results to technical and non-technical stakeholders.