Long Tail CAT Expert

About This Opportunity

We are looking for a Long Tail CAT Expert, based in Chicago, IL, Alpharetta, GA or O'Fallon, MO.

The NA Catastrophe Management team leads and owns accumulation topics across North America — encompassing framework development, implementation, and monitoring — while serving as the regional center of expertise for emerging risk analysis and risk mitigation strategy. Our team is dedicated to ensuring Allianz is well‑positioned for an uncertain future, combining deep technical capabilities with a forward‑looking mindset to drive rapid progress and meaningful impact across the organization.

Reporting to the Regional Head of CAT Management, North America, the Long Tail CAT Expert will play a key role in enabling and implementing the Allianz Commercial North America Nat Cat and Capacity Management strategy. You will align with North America Lines of Business, global and local leaders, and various finance functions to ensure that LoBs properly utilize available capacity and communicate updates to the CTO.

You will conduct related management reporting and measure performance through KPIs, while working to improve our overall strategy, tools and processes. You must be able to work independently with very limited guidance in complex areas and situations.

• Manage long tail CAT modelling, including creating local models and developing data pipelines and API calls.
• Develop and implement the North America Nat Cat Capacity Management strategy for long tail accumulations, including capacity management and risk appetite specific to long tail lines.
• Drive innovation and change related to modelling upgrades and enhance other tools, working closely with global teams to ensure alignment.
• Develop upgraded tools to better enable capacity steering and support long tail underwriting.
• Organize and supervise model runs and reviews.
• Work with CTO employees to run catastrophe loss modelling reports and prepare regular and ad‑hoc data extracts and reports for monitoring global loss potential, including portfolio analyses, CAT limit monitoring, and supporting global business steering.
• Cooperate closely with Product Leaders and Regional Underwriting specialists to support defining the risk appetite and capacity steering.
• Collaborate and coordinate across LoBs, cross‑functional and cross‑geographical senior level management, especially with the Global Accumulation and CAT management team, to define scope, agree on time frames and execute deliverables with internal and external clients, with minimal additional guidance for ad‑hoc data, reporting and project‑related tasks.
• Define and establish interfaces to neighboring teams and create efficient work processes (e.g., LoBs, Global Pricing, and other functions) to support business steering, portfolio management, and data quality improvements.
• Activate and leverage existing resources across the business to develop cross‑collaboration, manage relationships to enable diverse groups to collaborate and achieve sustainable outputs.
• Coaching other CTO employees in global loss modelling activities and related analyses, including using in‑depth knowledge of model methodology and function to explain and validate modelled loss output.
• Lead long‑tail accumulation modelling using industry‑standard tools, including scenario design, industry‑relationship mapping, and the simulation of accumulation events.
• Assess litigation‑based and industry‑wide exposure pathways, connecting model concepts (e.g., causation chains, litigation agents, culpability structures) to real‑world long‑tail claim behaviors.
• Own the data augmentation process, ensuring accurate enrichment of portfolios with granular industry and turnover coding, and integrate data from multiple internal systems to support robust model performance.
• Interpret model outputs expertly, including probabilistic and stochastic simulations, translating systemic risk results into meaningful business insights for long‑tail portfolios.
• Enable technical integration of model results, supporting ingestion into internal analytics environments (APIs, Databricks, Power
  
  BI) for consistent global usage.