Develop and apply predictive models to assess portfolio performance, risk metrics, and profitability.
Conduct scenario analysis to support strategic decision-making and capital allocation.
Identify trends, outliers, and opportunities for portfolio improvement using advanced analytics.
Collaborate with underwriting leadership to translate insights into actionable strategies.
Prepare and structure underwriting data (treaty, facultative, exposure, premium, loss) for use in a web-based portfolio management tool.
Design stored procedures, data pipelines, and APIs to support front-end development.
Ensure data integrity, consistency, and usability across systems.
Evaluate and enhance existing data workflows and reporting processes.
Automate data validation, cleansing, and transformation tasks.
Support the development of scalable data infrastructure for underwriting strategies.

Certified Specialist in Predictive Analytics (CSPA) or similar analytics credentials preferred.
Experience in reinsurance underwriting, actuarial analysis, catastrophe exposure modeling, or portfolio management analytics.
Strong command of SQL, Python, Microsoft Fabric, Databricks, and stored procedures.
Expertise in predictive modeling, machine learning, and statistical analysis.
Experience with cloud platforms (preferred: Azure), API development, and data automation tools.
Excellent communication skills with the ability to explain complex analytical concepts to non-technical stakeholders.
Highly independent, resourceful, and capable of thriving in a fast-paced environment with rapid turnaround expectations.
Strong attention to detail, problem-solving orientation, and a proactive “can-do” mindset.

Quantitative Reinsurance Analyst

Key skills