Head of Specialty Exposure Management
$200,000–$240,000 year
HybridNew Jersey, United States
Job Summary
Develop and maintain Ascot's View of Risk for all non-natural catastrophe classes, ensuring a consistent, robust, and commercially relevant approach across applicable lines of business. Lead the Exposure Management team in day-to-day activities, including pre- and post-bind modelling, monthly portfolio production, and reporting on both gross and net of reinsurance positions. Partner closely with underwriting teams to optimize the deployment of exposure capacity on a risk-adjusted return basis. Manage relationships with outsourcing partners, particularly those supporting data capture, and ensure service delivery aligns with Ascot's quality, accuracy, and timeliness expectations. Establish, maintain, and continuously improve data standards to support high-quality exposure management analysis and reporting. Own the completeness, accuracy, and integrity of exposure data, modelling outputs, and portfolio results. Prepare and present non-natural catastrophe exposure and modelled loss positions to the Exposure Management Committee, underwriting teams, and other senior stakeholders, with clear insight into portfolio movements, material drivers, and group-level implications. Lead regulatory reporting for relevant classes, ensuring submissions are accurate, timely, and completed in partnership with underwriting and senior management stakeholders. Serve as a key stakeholder in the use, enhancement, and future development of Exposure Management tools, platforms, and related projects. Expand advanced analytics capabilities to strengthen the Group Exposure Management function and improve the quality, speed, and relevance of portfolio insights. Contribute ideas and analytical insight to support the continual improvement of Ascot's regulatory ratings and risk management outcomes. Drive the ongoing enhancement and streamlining of Exposure Management capabilities, processes, controls, and workflows. Identify opportunities to leverage AI, automation, and traditional development capabilities to improve non-natural catastrophe processes and analytical efficiency. Model The Ascot Way in every aspect of leadership by fostering an inclusive, collaborative, entrepreneurial, and accountable culture grounded in excellence, integrity, resilience, and a passion to find a better way.
Required Qualifications
- Bachelor's degree
- Degree in a quantitative, actuarial, scientific, engineering, risk management, or related discipline
- Minimum of 10 years of relevant experience in catastrophe modelling, exposure management, or portfolio analytics within the insurance or reinsurance industry
- Demonstrated experience with Specialty lines, including Casualty, Professional Lines, Crisis Management, Marine, and other relevant non-natural catastrophe classes
- Proven ability to lead, develop, and motivate teams while influencing colleagues and senior stakeholders within a matrixed organization
- Deep technical knowledge of non-natural catastrophe exposure management techniques
- Experience with vendor and/or internally developed models
- Strong technical proficiency with relevant exposure management, data, and analytics systems, including SQL and related tools
- Strong understanding of non-natural catastrophe product lines, market dynamics, and emerging trends impacting specialty insurance portfolios
- Excellent planning, prioritization, and organizational skills, with the ability to manage multiple deliverables and deadlines in a complex environment
- Strong understanding of risk management and governance frameworks, including how exposure management contributes to portfolio oversight, controls, and decision making
- Practical understanding of underwriting risk, discipline, processes, and the commercial considerations that inform risk selection and portfolio management
- Ability to interpret, analyze, and clearly communicate model outputs, portfolio insights, and key risk drivers to technical and non-technical stakeholders
- Strong numerical, data handling, and analytical skills
- Strong understanding of AI, machine learning, predictive analytics, and data science applications within insurance, exposure management, and risk decisioning
- Hybrid work arrangement
Desired Qualifications
- Degree in a quantitative, actuarial, scientific, engineering, risk management, or related discipline
- Experience with vendor and/or internally developed models
- Strong understanding of AI, machine learning, predictive analytics, and data science applications within insurance, exposure management, and risk decisioning
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