Quantitative Reinsurance Analyst
About the position
About Everest: Everest is a global leader in risk management, rooted in a rich, 50+ year heritage of enabling businesses to survive and thrive, and economies to function and flourish. We are underwriters of risk, growth, progress and opportunity. We are a global team focused on disciplined capital allocation and long-term value creation for all stakeholders, who care deeply about our impact on communities and the wider world. Position Overview: As a Quantitative Reinsurance Analyst, you will serve as the analytical engine behind underwriting strategy. You’ll build predictive models, analyze portfolio risk, and uncover performance insights that guide strategic decision-making. You will prepare and engineer underwriting data—treaty, facultative, exposure, premium, and loss data—and power a web-based portfolio management tool that leaders rely on. You’ll streamline data workflows, automate reporting processes, and enhance the organization’s analytics infrastructure. Your strong SQL, Python, and Databricks skills will help you design scalable pipelines, APIs, and stored procedures, while your predictive modeling expertise enables you to identify trends, outliers, and opportunities to enhance portfolio performance. This is a hybrid position based in either our Warren, NJ or New York City office working 3 days onsite, 2 remote.
Responsibilities
• Predictive Analytics & Portfolio Optimization (Primary Focus) 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.
• Data Engineering & Web Tool Support 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.
• Process Improvement & Automation 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.
Requirements
• 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.
Benefits
• All offers include access to a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, 401k match, retirement savings plan, paid holidays and paid time off (PTO).
Apply tot his job
Apply To this Job
About Everest: Everest is a global leader in risk management, rooted in a rich, 50+ year heritage of enabling businesses to survive and thrive, and economies to function and flourish. We are underwriters of risk, growth, progress and opportunity. We are a global team focused on disciplined capital allocation and long-term value creation for all stakeholders, who care deeply about our impact on communities and the wider world. Position Overview: As a Quantitative Reinsurance Analyst, you will serve as the analytical engine behind underwriting strategy. You’ll build predictive models, analyze portfolio risk, and uncover performance insights that guide strategic decision-making. You will prepare and engineer underwriting data—treaty, facultative, exposure, premium, and loss data—and power a web-based portfolio management tool that leaders rely on. You’ll streamline data workflows, automate reporting processes, and enhance the organization’s analytics infrastructure. Your strong SQL, Python, and Databricks skills will help you design scalable pipelines, APIs, and stored procedures, while your predictive modeling expertise enables you to identify trends, outliers, and opportunities to enhance portfolio performance. This is a hybrid position based in either our Warren, NJ or New York City office working 3 days onsite, 2 remote.
Responsibilities
• Predictive Analytics & Portfolio Optimization (Primary Focus) 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.
• Data Engineering & Web Tool Support 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.
• Process Improvement & Automation 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.
Requirements
• 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.
Benefits
• All offers include access to a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, 401k match, retirement savings plan, paid holidays and paid time off (PTO).
Apply tot his job
Apply To this Job