Senior Actuary

Drive End-to-End Actuarial Analyses: Take full ownership of end-to-end analyses—from data gathering, cleansing, and modeling to delivering actionable presentations—managing projects from framing through to impact with minimal oversight.

Advance Pricing & Reserving Models: Independently build, maintain, and refine commercial auto pricing and reserving models to quantify expected losses and support Waymo's insurance and risk-financing strategies.

Champion Automation & AI Tooling: Proactively modernize and automate actuarial workflows, adopting AI-assisted coding, analytical tools, and programmatic data pipelines to scale team leverage.

Quantify Autonomous Driving Risks: Develop innovative quantitative metrics and methodologies to quantify novel risks and benchmark the safety performance of the Waymo Driver.

Build Scalable Data Pipelines: Extract, curate, and cleanse large, complex datasets from internal and external sources using scripting languages such as R, Python, and SQL.

Collaborate Cross-Functionally: Partner closely with Safety, Engineering, Product, Legal, and Finance to translate complex business and technical questions into tractable actuarial problems and deliver clear risk insights.

Institutionalize Best Practices: Establish reproducible modeling standards, document automated pipelines, and mentor teammates on modern actuarial and technical practices.

FCAS (Fellow of the Casualty Actuarial Society) strongly preferred. ACAS will be considered for exceptional candidates with standout technical and domain depth.

Strong commercial instincts with a proven ability to translate ambiguous business problems into structured technical analyses, synthesize findings, and provide high-impact risk insights.

Highly experienced actuary with a proven track record in casualty pricing, reserving, or risk modeling (commercial auto / transportation lines strongly preferred).

Fluent in R or Python, with advanced proficiency in SQL, spreadsheet modeling (Google Sheets / Excel), and data visualization tools.

Bachelor’s or Master’s degree in Actuarial Science, Statistics, Mathematics, Data Science, Economics, or a related quantitative field.

Strong predisposition toward process automation and proven ability to rapidly learn, adapt, and leverage new AI tools, software libraries, and modern analytical platforms.

Proven ability to scope ambiguous problems, research solutions, and execute independently with a "fire-and-forget" level of reliability.Exceptional ability to articulate complex quantitative findings and risk trade-offs clearly to technical, non-technical, and executive stakeholders alike.

Fully credentialed FCAS.

Advanced degree (MS / PhD) in Statistics, Data Science, Quantitative Finance, or a related field.

Hands-on experience integrating modern AI/LLM tools, machine learning libraries, or advanced statistical modeling into actuarial or insurance data workflows.

CERA (Chartered Enterprise Risk Analyst) designation or extensive ERM framework experience.

Demonstrated experience modeling risk for autonomous vehicles, rideshare fleets, novel mobility concepts, or complex commercial auto programs.