Underwriting Analytics VP — Data-Driven Portfolio Insights

Guy Carpenter; Morristown (NJ); Hybrid; USD 105,000 - 193,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Guy Carpenter seeks a talented data-science professional to join its Underwriting Analytics team. Based in any office, this hybrid role requires three days in the office weekly and blends data science, underwriting, and business strategy.

You will build models, apply ML, and translate questions into scalable analytics, partnering with underwriting, broking, actuarial, catastrophe modeling, and portfolio management teams. Marsh-backed firm offers growth and opportunity.

Qualifications

• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Actuarial Science, Engineering, or another quantitative discipline.
• 3–6 years of relevant experience in data science, advanced analytics, or quantitative modeling.
• Prior insurance industry experience at a carrier, reinsurer, broker, or data/analytics vendor.
• Demonstrated experience working with insurance datasets and business problems.
• Strong programming skills in Python and SQL; familiarity with R is a plus.
• Experience building and validating predictive or diagnostic models using statistical and machine learning techniques.
• Strong grounding in probability, statistics, model evaluation, and analytical problem-solving.
• Ability to communicate technical concepts effectively to underwriting and business stakeholders.
• Strong attention to detail, sound judgment, and the ability to manage multiple priorities.

Responsibilities

• Develop and enhance analytical models, decision tools, and data products that support underwriting and portfolio management objectives.
• Apply statistical, machine learning, and data mining techniques to large internal and external datasets to identify patterns, performance drivers, and emerging risk insights.
• Partner with underwriting, broking, actuarial, catastrophe modeling, and portfolio management teams to translate business questions into scalable analytical solutions.
• Build models and analytical frameworks for use cases such as risk segmentation, portfolio monitoring, performance attribution, propensity analysis, anomaly detection, and underwriting optimization.
• Design and execute exploratory data analysis to assess portfolio characteristics, underwriting outcomes, loss experience, and market trends.
• Engineer features from structured and semi-structured insurance datasets, including exposure, submission, pricing, claims, and third-party data sources.
• Support productionization of analytical workflows by contributing to model validation, documentation, version control, testing, and monitoring.
• Create clear and compelling visualizations, summaries, and presentations that communicate technical findings to both technical and non-technical stakeholders.
• Contribute to the continuous improvement of underwriting analytics capabilities, data pipelines, and modeling standards across the team.
• Stay current on emerging methods in machine learning, optimization, and applied analytics relevant to underwriting and reinsurance decision-making.

Skills

Data science

Machine learning

Analytics

Python

SQL

R

Education

Bachelor’s degree in quantitative field

Tools

Python

SQL

R

Job description

Guy Carpenter seeks a talented data-science professional to join its Underwriting Analytics team. Based in any office, this hybrid role requires three days in the office weekly and blends data science, underwriting, and business strategy.

You will build models, apply ML, and translate questions into scalable analytics, partnering with underwriting, broking, actuarial, catastrophe modeling, and portfolio management teams. Marsh-backed firm offers growth and opportunity.