Full-Time
Associate Actuary
Updated on 8/23/2026
Wildfire Defense Systems
Compensation Overview
$74k - $90k/yr
Remote in USA
Hybrid
Remote or hybrid arrangements are available under company policy; occasional travel may be required for meetings, conferences, hearings, or client engagements.
Bachelor's, Master's
Category
 Finance & Banking (1) |
|---|
Required Skills
Power BI
MLOps
Microsoft Azure
Python
Data Visualization
R
Neural Networks
Git
Apache Spark
SQL
Machine Learning
Version Control
Tableau
AWS
VBA
Databricks
Looker
Snowflake
Google Cloud Platform
Excel/Numbers/Sheets
Financial Modeling
Requirements
- A bachelor's degree in Actuarial Science, Mathematics, Statistics, Data Science, Computer Science, Economics, or a closely related quantitative field is required.
- Active pursuit of the Casualty Actuarial Society Fellowship designation is required.
- Three or more years of progressive actuarial experience in property and casualty insurance and/or reinsurance pricing is required.
- Demonstrated experience building and deploying predictive models and pricing tools in a commercial or specialty insurance environment is required.
- Advanced proficiency in Python is required.
- Strong SQL skills for data extraction, transformation, and analysis from relational databases are required.
- Strong command of property and casualty actuarial pricing fundamentals, including loss development, trend analysis, credibility theory, exposure rating, retrospective rating, and experience modification, is required.
- A solid understanding of reinsurance pricing concepts, including burning cost, experience rating, exposure rating, and swing plans, is required.
- Knowledge of catastrophe modeling concepts and their interaction with property pricing and portfolio management is required.
- An understanding of insurance accounting, loss reserving concepts, and their relationship to pricing adequacy is required.
- Familiarity with actuarial standards of practice and professional guidelines relevant to pricing is required.
- Experience with machine learning frameworks and techniques, including generalized linear models, gradient boosting machines, gradient boosting, random forests, clustering, neural networks, and model ensembling, is required.
- Familiarity with MLOps concepts, including model versioning, monitoring, feature stores, and deployment pipelines, is required.
- Advanced proficiency in Microsoft Excel, including Power Query, pivot tables, and financial modeling, is required.
- Experience with version control systems and collaborative development workflows is required.
- Strong analytical and quantitative skills, attention to detail, accuracy, and numerical reasoning are required.
- The ability to identify, frame, and solve complex ambiguous problems using structured thinking and creative approaches is required.
- The ability to synthesize macro- and micro-level perspectives into actionable insights from complex data is required.
- The ability to translate complex technical results into clear, actionable insights for non-technical audiences is required.
- The ability to present findings and recommendations to senior leadership, underwriting management, regulatory bodies, and external partners is required.
- The ability to collaborate and build relationships effectively in cross-functional, matrix environments is required.
- The ability to provide constructive mentorship and training to junior team members is required.
- Strong organizational, prioritization, and time-management skills are required.
- A commitment to actuarial professionalism and ethical conduct is required.
- The ability to navigate existing systems and processes efficiently is required.
Responsibilities
- Design, build, and validate predictive pricing models using statistical and machine learning methods for property and casualty and reinsurance lines.
- Develop and maintain end-to-end pricing pipelines from raw data ingestion and feature engineering through model training, validation, deployment, and monitoring.
- Apply credibility theory, loss development, trend analysis, and exposure rating with data science techniques to produce rate indications.
- Develop pricing tools and actuarial models supporting price adequacy estimation, rate-change measurement, and portfolio segmentation.
- Automate recurring pricing workflows and reporting using Python, R, or SQL.
- Maintain version control and documentation for models, code, and assumptions in accordance with company standards and actuarial professionalism guidelines.
- Perform regular rate indications for assigned states and programs using loss ratio, pure premium, and experience rating approaches.
- Recommend rate actions focused on long-term profitability, market competitiveness, and regulatory feasibility.
- Research peer-company filings and develop actuarially supportable rates in emerging or data-sparse segments.
- Perform portfolio-level and individual account or treaty pricing analyses across property, casualty, specialty, and reinsurance lines.
- Assist senior staff with reviewing and pricing new program opportunities, facultative submissions, and treaty structures.
- Identify profitable areas for growth and underperforming segments for re-underwriting, contraction, or exit.
- Develop segmental and trend analyses to support underwriting decisions and strategic planning.
- Monitor pricing performance metrics, including rate change, price adequacy, loss-ratio emergence, and plan-versus-actual comparisons.
- Design and maintain dashboards and reporting tools that provide pricing intelligence to underwriting teams and senior leadership.
- Conduct experience studies, parameter reviews, and assumption updates on a defined schedule; present findings and recommendations to key committees.
- Support reserve reviews for assigned segments and respond to ad hoc data calls from internal and external stakeholders.
- Coordinate with Underwriting, Claims, Reserving, Exposure Management, and the Managing Actuary so pricing reflects relevant loss, exposure, and operational information.
- Provide training and technical guidance to underwriters on pricing methodology, rate-change requirements, and model outputs.
- Present findings, model results, and recommendations to actuarial management, underwriting teams, compliance officers, MGU/MGA partners, and regulators.
- Ensure data quality, integrity, and completeness in pricing tools; identify data gaps and champion improvements.
- Identify opportunities to improve pricing processes, methodologies, and data infrastructure, and contribute to or lead their delivery.
- Maintain pricing model documentation at the required frequency, obtain managerial sign-offs, and adhere to model-governance standards.
- Apply the company's pricing quality-assurance process and support underwriting controls related to pricing and regulatory principles.
- Keep current with industry best practices, emerging data science techniques, actuarial initiatives, and regulatory changes.
- Support colleagues and contribute to overall team and business objectives.
- Pursue actuarial examination progress toward the FCAS designation and engage in ongoing professional development.
Desired Qualifications
- A master's degree in Actuarial Science, Statistics, Data Science, Applied Mathematics, or a related discipline is strongly preferred.
- ACAS or near-ACAS standing is preferred.
- Experience preparing rate filings, interacting with Departments of Insurance, and supporting regulatory compliance is preferred.
- Familiarity with MGU/MGA, program, treaty, or facultative reinsurance business structures is preferred.
- Prior experience working in or alongside data engineering or data science teams is preferred.
- Proficiency in R is strongly preferred.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform and big-data tools such as Spark, Databricks, or Snowflake is preferred.
- Familiarity with data visualization and business intelligence tools such as Tableau, Power BI, or Looker is preferred.
- Supplemental credentials such as CPCU, ARe, CERA, or formal data science certifications are a plus.
- VBA or Excel automation experience is a plus.