Principal Data Scientist

SUMMARY:

The Principal Data Scientist is a highly experienced individual contributor who serves as a technical authority in applying advanced analytics and machine learning to complex P&C insurance problems, including underwriting, pricing, and risk selection. This role owns the end‑to‑end analytical lifecycle, from problem formulation and model development through deployment, monitoring, and governance. Partners closely with Actuarial, MLOps, and IT to deliver scalable, production‑ready solutions. The Principal Data Scientist ensures long‑term model performance through rigorous validation, drift monitoring, and audit‑ready documentation, while advancing analytical best practices and evaluating emerging techniques relevant to commercial P&C insurance.

RESPONSIBILITIES/TASKS:

• Acquires, organizes, and cleanses structured and unstructured data.
• Conducts in-depth analysis to uncover trends, risks, and business opportunities.
• Applies statistical modeling, machine learning, and advanced analytics to develop predictive and prescriptive solutions.
• Evaluate solution performance using statistically rigorous methods and measure the impact to business outcomes.
• Collaborate with MLOps and IT partners to transition solution prototypes from pilot validation into production environments.
• Ensures ongoing model health through post‑deployment monitoring, drift detection, and audit‑compliant governance practices.
• Creates and communicates results to senior level audiences of varying backgrounds, using business-facing presentations, reports, and dashboards.
• Author and maintain comprehensive technical documentation for data lineage, codebases, results, and production changes.
• Provides technical and project guidance, including peer review of work, for data science team.
• Leads the evaluation of new analytic tools and processes.
• Drivesinvestigation and adoption of advanced machine learning and AI innovations.

EDUCATION:

Bachelor’s Degree in Data Science, Statistics, Mathematics, Operations Research, Actuarial Science, Computer Science, Engineering, Physics or related technical field required. Advanced degree preferred.

EXPERIENCE:

10 years of experience in data science or related advanced analytics domains, including research and teaching, with 3+ years of technical leadership.

REQUIRED SKILLS/KNOWLEDGE/ABILITIES:

• Broad experience supporting underwriting functions within multi-line commercial P&C insurance settings, including 3+ years of loss modeling for General Liability (aka Casualty) or Commercial Property.
• Demonstrated expertise using Poisson, Gamma, and Tweedie distributions to build loss ratio, pure premiu