Wdscareers

Wdscareers

Associate Actuary

Remote (United States)

Sponsorship not specifiedDetected 20 days ago
PythonGitSQLSnowflakeDatabricksAWSGCPAzureCloud PlatformsMachine LearningSparkData EngineeringData ScienceData VisualizationMLOpsStatisticsComplianceFinancial ModelingAccountingExcelProcess ImprovementControlsResearchLeadership

About the role

  • 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).
  • Purpose and Scope of Position The Associate Actuary is a pivotal technical and collaborative role within WD InsurTech's Actuarial Pricing & Analytics function.
  • Apply credibility theory, loss development, trend analysis, and exposure rating in combination with data science techniques to produce robust rate indications.

Responsibilities

  • Develop and maintain end-to-end pricing pipelines, from raw data ingestion and feature engineering through model training, validation, deployment, and monitoring.
  • Develop pricing tools and actuarial models that support estimation of price adequacy, rate change measurement, and portfolio segmentation across all assigned lines of business.
  • Maintain version control and documentation of models, code, and assumptions in alignment with company standards and actuarial professionalism guidelines.
  • Rate Indications & Regulatory Filings Perform regular rate indications for all assigned states and programs using standard actuarial methods, including loss ratio, pure premium, and experience rating approaches.
  • Research peer company filings and develop actuarially supportable rates in emerging or data-sparse segments.
  • Portfolio & Transactional Pricing Perform portfolio-level and individual account/treaty pricing analyses across property, casualty, specialty, and reinsurance lines.
  • Develop segmental and trend analyses to support underwriting decisions and strategic planning.
  • Design and maintain dashboards and reporting tools that deliver actionable pricing intelligence to underwriting teams and senior leadership.
  • Support reserve reviews for assigned segments and respond to ad hoc data calls from internal and external stakeholders.
  • Clearly and concisely present findings, model results, and recommendations to diverse audiences including senior actuarial management, underwriting teams, compliance officers, MGU/MGA partners, and regulators.

Requirements

  • Prolonged periods sitting at a desk and working on a computer Must be able to lift 15-lbs.
  • Maintain pricing model documentation at required frequency, obtaining appropriate managerial sign-offs and adhering to model governance standards.

Nice to have

  • loss development, trend analysis, credibility theory, exposure rating, retrospective rating, and experience modification.
  • Solid understanding of reinsurance pricing concepts including burning cost, experience rating, exposure rating, and swing plans.
  • Knowledge of catastrophe modeling concepts and their interaction with property pricing and portfolio management.
  • Understanding of insurance accounting, loss reserving concepts, and their relationship to pricing adequacy.
  • Familiarity with actuarial standards of practice (ASOPs) and professional guidelines relevant to pricing.
  • Data Science & Programming Advanced proficiency in Python required.
  • Proficiency in R strongly preferred.
  • Strong SQL skills for data extraction, transformation, and analysis from relational databases.

Skills

  • About Wildfire Defense Systems, Inc.
  • WDS provides these industry - leading services to insurer clients and their policy holders across a 22-state service area.

Benefits

  • Pricing Model Development & Data Science Job RequirementsDesign, build, and validate predictive pricing models using statistical and machine learning methods, tailored to P&C and reinsurance lines.

Equal opportunity

  • WD InsurTech is an equal opportunity employer.

This listing is sourced directly from Wdscareers's careers page and normalized into a canonical job model.