Actuary

Arbol is a global climate risk coverage platform and Fin Tech company offering full-service solutions for businesses analyzing and mitigating exposure to climate risk. Our products provide parametric coverage that pays out based on objective data triggers rather than subjective loss assessment, and our ecosystem delivers climate data infrastructure, scalable product development, artificial‑intelligence‑powered underwriting, blockchain‑enabled efficiencies, and non‑traditional risk capacity.

We are building an AI‑enabled homeowners insurance platform focused on underserved coastal and catastrophe‑exposed markets. We need a talent actuarial leader to drive pricing, reserving, reinsurance analytics, and portfolio analytics while working side‑by‑side with our AI and engineering teams to build the next generation of actuarial workflows.

In this role you will primarily work on homeowners’ insurance in coastal southern states, with opportunities to support expansion into new lines and territories. Your focus will be on translating complex actuarial judgment, workflows, and analyses into scalable AI‑enabled tools that enhance speed, rigor, and decision‑making across the business. The ideal candidate owns the work, is fluent in tools such as Excel and Python, and is excited to work at the intersection of actuarial science, insurance operations, and applied AI.

• Develop rate indications and pricing analyses (e.g., territory, deductible, and other rating factors).
• Monitor rate adequacy, loss trends, inflation impacts, and emerging experience.
• Build and maintain pricing tools, exhibits, and documentation used for internal decisions and regulatory filings.

• Perform quarterly reserve analyses (e.g., triangles, ultimate loss selections, IBNR, diagnostics) for homeowners and related lines.
• Monitor loss emergence, claim severity/frequency trends, and CAT vs non‑CAT performance.
• Partner with Claims and Finance to reconcile results, investigate drivers, and improve data quality.

• Build recurring dashboards to monitor portfolio performance and emerging trends.
• Work with AIR and other catastrophe model output to assess exposure concentrations, catastrophe load, and risk‑adjusted returns.
• Evaluate reinsurance program impacts and support related reporting and analytics.
• Support scenario analyses, including catastrophe load, trend, rate change, and mix sensitivities.

• Learn Lilypad's actuarial processes end‑to‑end and identify automation opportunities (e.g., gross‑to‑net loss calculations, reserve workflows).
• Serve as a bridge between the actuarial and AI/engineering teams, translating actuarial logic into requirements that can be built into automated tools.
• Write and maintain Python‑based workflows to streamline recurring analyses; collaborate with the AI team on tool development.

• Collaborate with Underwriting, Claims, Finance, Data/Engineering, and Leadership on special projects (product changes, underwriting guidelines, new territories/segments, vendor evaluation, etc.).
• Contribute to process improvements, automation, and better controls/documentation.

• 5‑8 years of P&C actuarial experience; ACAS/FCAS credential.
• High ownership and self‑starter mindset; able to drive work forward with limited structure.
• Strong proficiency in Excel and Python, with the ability to build clean, repeatable analyses.
• Strong analytical and problem‑solving skills; able to communicate findings clearly to non‑technical stakeholders.
• Bachelor’s degree in Actuarial Science, Mathematics, Statistics, or a related quantitative field.

• Experience building repeatable analytics (dashboards, automated data pulls, version‑controlled workflows).
• Homeowners experience, including catastrophe exposure management, weather/CAT analytics, inflation/trend work, or rate filing support.
• Experience with reserving methods (chain ladder, BF, Cape Cod style approaches) and/or pricing indications.
• Knowledge of policy/claims data structures and common insurance KPIs.