Sr P&C Data Scientist

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.

Key Responsibilities

Pricing & Insurance Analytics

• 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

Modeling & Data Science Execution

• 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

Data & Technical Skills

• 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

Business Partnership & Communication

• 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

Coaching & Continuous Improvement

• 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

Required Qualifications

• 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

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