Head of Catastrophe Modeling

About Wildfire Defense Systems, Inc.

Wildfire Defense Systems (WDS) is the North American leader in insurer wildfire services, combining professional wildfire consulting and loss intervention services with Qualified Insurance Resources (QIR). Founded in 2001 to fulfill initial-attack assignments for the US Forest Service, the company added professional services support in 2005 and launched wildfire loss-intervention programs for insurers in 2008.

WDS Wildfire Loss Intervention Service (WDS Service) applies a comprehensive approach to reducing risk in catastrophic exposure on an industry scale, decreasing the average annual loss (AAL) for our insurer clients, and providing peace of mind to their policy holders during wildfire events. WDS provides these industry-leading services to insurer clients and their policy holders across a 22-state service area.

Purpose and Scope of Position

The Head of Catastrophe Modeling leads Wildfire Defense Systems’ efforts to quantify wildfire risk and demonstrate the loss-reduction value of WDS’s services to insurance partners. This role translates WDS’s field and operational data into credible, model-driven insights that support carrier relationships, business growth, and operational decision-making. A major responsibility of this role is to design, develop, and maintain proprietary internal catastrophe models and contribute to risk and pricing modeling.

This position sits within the Data Science Department and reports to the Data Science Manager. The Head of Catastrophe Modeling owns the development, validation, and application of wildfire catastrophe models and analytics across WDS’s enrolled property portfolio in the United States and Canada. They serve as WDS’s subject matter expert on wildfire hazard, structure vulnerability, and loss estimation. They evaluate and work alongside industry-standard vendor models, build proprietary analytics from WDS’s unique data, and communicate findings to executive leadership, insurance carriers, and reinsurance partners. The role collaborates with data science colleagues and partners closely with actuarial, operations, product, and client-facing teams. It also builds and leads a team of modeling and analytics professionals as the function grows.

Organizational Relationship

This position technically reports to the Data Science Manager. The Head of Catastrophe Modeling will be a WDS employee who works closely with other WD Companies.

Duties and Responsibilities

Your duties may include, but are not limited to:

• Design, develop, calibrate, validate, and maintain proprietary catastrophe models focused on wildfire, while incorporating secondary perils such as fire following quake and other risk related to the company's portfolio.
• Develop methodologies for event generation, hazard characterization, vulnerability modeling, and financial loss estimation.
• Research emerging catastrophe risks and continuously enhance modeling methodologies.
• Analyze accumulation risk and concentration management at geographic, peril, and portfolio levels.
• Produce catastrophe risk metrics including AAL, EP curves, TVaR, PML, and stress-test scenarios.
• Translate catastrophe model outputs into loss cost assumptions and catastrophe loadings for insurance pricing models.
• Partner with actuarial, underwriting, and product teams to incorporate catastrophe risk into rate indications and pricing strategies.
• Lead catastrophe analytics supporting reinsurance purchasing decisions.
• Develop pricing methodologies for ceded and assumed reinsurance transactions.
• Support strategic planning, capital management, and growth initiatives through quantitative risk analysis.

Job Requirements

Basic Qualifications (i.e. education, certifications, etc…)

Educational Qualifications

• Advanced degree (MS or PhD) in Statistics, Actuarial Science, Mathematics, Engineering, or a related quantitative field.

Experience

• 7+ years of P&C insurance experience related to catastrophe modeling, exposure and risk management, pricing/reserving, and reinsurance strategy.
• Familiarity with functionality and I/O of major CAT model vendors (Verisk, Cotality, RMS).
• Experience supporting insurance pricing, portfolio management, and reinsurance negotiations.

Knowledge, Skills, Abilities, & Experience

• Advanced statistical modeling techniques.
• Proficiency in Python, R, SQL, or comparable analytical programming languages.
• Strong understanding of catastrophe risk concepts, probabilistic modeling, and insurance/reinsurance structures.
• Strong communication skills with the ability to explain complex technical concepts to non-technical audiences.
• Knowledge of geospatial analytics, machine learning, and climate risk modeling techniques.

Location

This position is eligible for a hybrid or remote work arrangement, subject to WDS flexible work policy and business needs. Occasional travel may be required for team meetings, industry conferences, regulatory hearings, or client engagements. The role operates in a standard office or remote office environment with extended periods of computer use.

Physical Requirements

• Prolonged periods sitting at a desk and working on a computer
• Must be able to lift 15-lbs.

This job description should not be construed as an exhaustive statement of duties, responsibilities or requirements, but a general description of the job. Nothing contained herein restricts WDS rights to assign or reassign duties and responsibilities to this job at any time.

Wildfire Defense Systems, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

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