Sr P&C Data Scientist

Brookfield Wealth Solutions, Ltd•Los Angeles, CA

1d•$92,000 - $160,000

About The Position

The Senior P&C Data Scientist owns the development and improvement of analytical models and insights that inform pricing, underwriting, and portfolio management decisions. This role applies statistical, machine learning, and data analysis techniques to insurance data to improve risk segmentation and rate adequacy, supporting profitable growth across products and locations. Operating with a high level of independence and accountability, the role partners closely with pricing actuaries, underwriting, claims, distribution, product, and IT professionals to translate business questions into analytical solutions, implement models into pricing workflows, and monitor performance over time. The Senior P&C Data Scientist also mentors less‑experienced team members and contributes to the continued maturation of the pricing analytics function.

Requirements

Bachelor’s degree in mathematics, statistics, actuarial science, computer science, data science, or a related quantitative field
Five years of relevant experience in data science, analytics, pricing, actuarial, or related quantitative roles. A master’s degree may be considered in lieu of one to two years of experience
Advanced proficiency in analytical programming languages and tools (e.g., SQL, Python, R)
Experience working with large, complex datasets and applying statistical or machine learning methods to real‑world business problems
Strong analytical judgment, problem‑solving ability, and communication skills
Proven ability to work independently and own complex analytical models
Applicants must be legally authorized to work in the United States. At this time, we are not able to sponsor or assume sponsorship of employment visas.

Nice To Haves

Significant experience in Property & Casualty insurance, particularly pricing, ratemaking, underwriting analytics, or actuarial support
Familiarity with several predictive modeling techniques (e.g., GLMs, tree‑based models, gradient boosting)
Familiarity with regulatory and governance considerations related to pricing and underwriting
Experience implementing and monitoring models in production or business workflows
Experience mentoring and reviewing the work of junior coworkers

Responsibilities

Develop, refine, and maintain analytical models supporting P&C pricing, including frequency, severity, pure premium, risk segmentation, persistency, and portfolio optimization models
Independently own pricing models translating analytical results into actionable recommendations
Apply insurance domain knowledge (e.g., coverage, exposure, underwriting rules, regulatory considerations) in model design, development, interpretation, and business use
Own the end‑to‑end analytical lifecycle for complex initiatives: data exploration, feature engineering, model building, validation, implementation, monitoring, and enhancement
Select and apply statistical and machine learning techniques appropriate for pricing use cases, balancing predictive performance, stability, interpretability, and regulatory considerations
Design and execute validation frameworks to assess model performance, stability, and business impact
Drive the implementation of models and analytical outputs into pricing and reporting workflows
Work independently with large, structured and semi‑structured datasets using SQL and analytical programming languages (e.g., Python or R)
Establish and uphold high standards for data quality, reproducibility, documentation, and version control
Follow model development best practices and model risk governance standards
Serve as a trusted analytics partner to actuarial, underwriting, distribution, and product stakeholders
Translate technical analyses into clear, actionable insights using appropriate visualizations and written summaries
Influence decision‑making by framing trade‑offs, risks, and opportunities using data‑driven narratives
Respond to feedback and iterate on analyses to better support business decisions
Present analytical findings to senior management and cross‑functional leadership
Mentor and provide technical guidance to P&C Data Scientist I and II team members through code reviews, modeling discussions, and project support
Contribute to the development of analytical standards, best practices, and reusable modeling frameworks
Stay current on P&C industry trends, pricing methodologies, and analytical best practices within P&C insurance
Proactively identify opportunities to improve models, processes, data usage, and business outcomes within the pricing analytics function