AVP/VP, Underwriting Analytics
$105,000–$192,500 year
HybridChicago, Illinois, United States or San Francisco, California, United States
Job Summary
Develop and enhance analytical models, decision tools, and data products supporting underwriting strategy and portfolio insights. Apply statistical, machine learning, and data mining techniques to large datasets to identify patterns, performance drivers, and emerging risk insights. Partner with underwriting, broking, actuarial, and portfolio management teams to translate business questions into scalable solutions. Engineer features from structured and semi-structured insurance datasets, including exposure, submission, pricing, and claims data. Design exploratory data analysis to assess portfolio characteristics and loss experience, then create visualizations and presentations for technical and non-technical stakeholders. Contribute to continuous improvement of analytics capabilities, data pipelines, and modeling standards while staying current on emerging methods in applied analytics. Work at the intersection of data science and business strategy to deliver decision support across the organization.
Required 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
- 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
- Must be available for at least three days a week in the office
- Advanced degree in a quantitative field
Desired Qualifications
- Familiarity with R
- Experience specifically in underwriting analytics, portfolio analytics, or insurance performance analytics
- Familiarity with commercial insurance and/or reinsurance concepts, underwriting workflows, and portfolio management practices
- Experience with methods such as GLMs, tree-based models, clustering, regularization, time series analysis, and anomaly detection
- Experience with exposure, policy, claims, pricing, or submission data in a P&C or specialty insurance context
- Familiarity with cloud-based analytics environments, model deployment practices, and modern data tooling
- Exposure to geospatial, catastrophe, or alternative risk datasets
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.