Director, P&C Analytics

Argo Group International Holdings, Inc.and American National, US based specialty P&C companies, (together known as BP&C, Inc.) are wholly owned subsidiaries of Brookfield Wealth Solutions, Ltd. ("BWS"), a New York and Toronto-listed public company. BWS is a leading wealth solutions provider, focused on securing the financial futures of individuals and institutions through a range of wealth protection and retirement services, and tailored capital solutions.

Job Description

The role will focus on building and managing a team responsible for the development, validation, and implementation of actuarial pricing models and advanced analytics solutions across all P&C lines of business. This role will work with leadership to establish the modeling strategy and governance framework to ensure the Actuarial Analysts and Data Scientists within P&C Operations are delivering innovative, accurate, and compliant pricing solutions that drive profitable growth.

The Director, P&C Actuarial Analytics & Pricing Models, is a strategic and innovative leader with the goal to bridge traditional actuarial science with modern data science techniques, empowering the team to develop cutting-edge pricing solutions while maintaining actuarial rigor and regulatory compliance.

The role will work onsite (5 days per week) at one of our office locations: Springfield, MO, Richmond, VA, Chicago, IL and Glenmont, NY. Note: The Des Moines, IA location is remote until the office is available.

ESSENTIAL FUNCTIONS:

• Provides clarity of the vision, strategy, growth, and development for pricing models and predictive analytics among all areas within P&C Operations (i.e., Underwriting, Product, Actuarial, ML Agencies, Marketing, SMG, Claims, Competitive Intelligence)
• Creates the appropriate documentation that allows stakeholders (i.e., executive management, regulators) to clearly understand the modeling methodologies, assumptions, and validation procedures for pricing and risk selection models within P&C Operations.
• Leads team to build and implement pricing models, predictive analytics solutions, and machine learning algorithms utilized by all areas within P&C Operations.
• Leads discussions with stakeholders from various business areas to translate their pricing and risk assessment needs by understanding data structures, determining model requirements, analyzing predictive variables, and evaluating model performance metrics.
• Monitors modeling projects that assist in translating complex statistical findings into easy-to-understand visuals and written summaries for non-technical audiences to ensure requirements and deadlines are met.
• Validates pricing algorithms, predictive models, and machine learning solutions developed by the Analytics teams for accuracy, stability, and business value.
• Monitors the models produced to ensure they remain compliant with regulatory requirements and actuarial standards of practice.

REQUIRED QUALIFICATIONS:

• Preferred Advanced degree in Actuarial science, Mathematics, Statistics, Data Science, or related quantitative field.
• 10 to 12 years of P&C experience with significant exposure to pricing and predictive modeling.

• Three to five years of supervisory/management experience leading technical teams. ACAS designation or FCAS preferred.
• Expert knowledge of P&C pricing methodologies including loss development, trend analysis, and rate indication techniques.
• Strong project management skills with ability to manage multiple concurrent initiatives.
• Excellent communication skills to present technical concepts to non-technical audiences.
• Strong Collaboration skills to works across functional Areas (Pricing, Underwriting, Product)
• Expert level coding skills with software (e.g., R, Python, SQL)
• Awareness of actuarial and statistical software (i.e. Emblem, Akur8).
• Familiarity within data visualization and model deployment tools (e.g., PowerBI, Tableau).

PREFERENCES:

* Advanced degree (MS/PhD) in Statistics, Data Science, or related field with focus on predictive modeling. Experience with modern machine learning techniques and their application to insurance pricing:

• Machine learning frameworks (TensorFlow, PyTorch, scikit-learn, XGBoost, GLM, Decision Tree, Random forest)
• Cloud computing platforms (AWS, Azure, GCP) for model deployment
• Version control and MLOps tools (Git, MLflow, Kubeflow)
• Real-time pricing APIs and model deployment pipelines
• Alternative data sources (telematics, IoT, external data)
• Knowledge of regulatory requirements and rate filing processes across multiple jurisdictions

The base salary range provided below is for hires in those geographic areas only and will be commensurate with candidate experience. Pay ranges for candidates in other locations may differ based on the cost of labor in that location. In addition to base salary, all employees are eligible for an annual bonus based on company and individual performance as well as a generous benefits package.