Waymo Senior Safety Management System Analytics Specialist at Waymo leading measurement and reporting of SMS performance. Develops metrics and translates data into executive recommendations to drive safety improvements.
Responsibilities
Develop Reliable Safety Performance Indicators: Design and refine SMS implementation, maturity, and effectiveness metrics grounded in industry best practices and international safety standards, assessing and maintaining metric quality and advising teams and leaders on proper metric interpretation and use.
Map & Synthesize Multi-Domain Safety Management Metrics: Collect, quality-assure, and synthesize quantitative and qualitative metrics across multiple business functions and trace them to the company’s top-line safety objectives.
Run SMS Performance Reporting Governance: Lead the processes and analytics workflows used to support executive leadership review of SMS performance data and aggregated trend analyses.
Translate Signals into Executive Decision Material: Partner with data science, operational, and safety teams across Waymo to distill complex multi-source data into clear, decision-oriented briefings, dashboards, and continual-improvement recommendations for senior leaders.
Drive Closed-Loop Action & Effectiveness Tracking: Monitor safety performance indicators against targets and thresholds; where indicators show adverse trends or fall short of targets, confirm an accountable owner is assigned and track action items through to verified closure and confirmed effectiveness.
Scale Analytics Tooling & Audit Readiness: Define requirements for data collection, visualization, and reporting tools that improve the reliability and scalability of SMS performance measurement, and support preparation for domestic and international regulatory audits and evaluations.
Qualification
A Bachelor’s degree in Data ScienceProficiency with modern data analyticsHands-on familiarity with automotive
Required
A Bachelor’s degree in Data Science, Computer Science, Engineering, Economics, Statistics, or a related scientific or analytic field.
Minimum 5 years of experience in data analytics, safety or operational performance measurement, or business/technical intelligence within complex engineering, financial, transportation, or safety-critical organizations.
Demonstrated expertise working with both quantitative and qualitative data and metrics, including developing metrics based on industry best practices or standards, evaluating and maintaining metric quality, and advising stakeholders on metric interpretation and limitations.
Proficiency with modern data analytics, visualization, and reporting tools (e.g., SQL, Python/R, BI dashboards, and data pipelines) to collect, validate, and communicate performance data to executive leadership and governance committees.
Proven ability to pull together and synthesize disparate metrics to drive continual improvement and verify the effectiveness of corrective actions.
Strong cross-functional collaboration and communication skills, with experience translating complex technical and operational signals into clear, actionable narratives for senior decision-makers without direct authority.
An advanced degree (Master’s or PhD) in Data Science, Computer Science, Engineering, Economics, Statistics, or a related scientific or analytic discipline.
Hands-on familiarity with automotive, transportation, or aviation Safety Management System frameworks and safety performance indicators.
Direct experience interpreting and implementing safety performance measurement requirements from vehicle, transportation, or aviation safety regulations and standards.
Experience leveraging Artificial Intelligence (AI) / Large Language Model (LLM) workflows or automated data pipelines to synthesize qualitative and quantitative safety signals, detect emerging trends, and streamline executive reporting.
Experience designing and running closed-loop performance governance processes, including threshold alerting, root-cause and CAPA tracking, and statistical or empirical verification of mitigation effectiveness.
Experience partnering with software/data engineering teams to define data schemas and business requirements for scalable internal analytics and reporting platforms.
