Safety Data Analyst

What You’ll Do

Develop, implement, and refine safety performance indicators, thresholds, and targets to proactively identify, assess, and manage safety risk across on-road and simulation-based data sources.

• Apply statistically sound methods to evaluate safety performance, quantify uncertainty, and support risk-based decision-making in complex, real-world operational contexts.
• Develop automated, production-ready analysis workflows that support continuous safety monitoring, milestone gating, incident response, and safety performance evaluation.
• Ensure performance monitoring approaches appropriately reflect real-world deployment exposure, evolving operational contexts, and relevant safety requirements.
• Balance analytical rigor with timeliness to support high-consequence, time-sensitive decisions.
• Evaluate data quality, uncertainty, bias, and limitations to ensure findings are statistically defensible and useful for decision-making.
• Support data visualization, reporting, and communication strategies that help technical teams, safety stakeholders, and executives understand insights, tradeoffs, and limitations.
• Partner cross-functionally with engineering, product, verification and validation, simulation, metrics implementation, and safety teams to integrate workflows and align on data-driven decisions.
• Maintain strong documentation of analytical methods, assumptions, workflows, requirements, safety metrics, and outputs to support traceability, collaboration, and regulatory readiness.
• Ensure continuity of knowledge through peer review, cross-training, shared analytical patterns, and reproducible workflows that reduce single-point dependencies.

What You’ll Need to Succeed

Advanced degree in Data Science, Computer Science, Math, or a closely related field:

• B.S. with 5+ years of experience, or
• M.S. with 3+ years of experience, or
• PhD with 1+ years of experience
• Proven experience in mechanical engineering, vehicle engineering, autonomous systems, robotics, or physics-based applications.
• Experience with vehicle and sensor systems, cloud-based data technology, data visualization, and statistical analytics.
• Strong background in applied statistics, safety analysis, risk estimation, or decision support.
• Experience working with complex, real-world datasets rather than only clean or purely academic data.
• Experience working with large-scale time-series data, vehicle data, sensor data, structured safety datasets, or other heterogeneous technical data sources.
• Proficiency in programming languages, particularly Python and SQL.
• Familiarity with agile development practices and continuous integration/deployment, including CI/CD workflows.
• Strong time management and organizational skills with the ability to prioritize tasks effectively.
• Excellent problem-solving skills with the ability to dissect complex issues and develop practical, creative solutions.
• Ability to communicate statistical and technical concepts clearly to diverse teams and stakeholders.
• Experience working in distributed teams and collaborating across different time zones.

Bonus Points

• Background applying statistics to engineering or physics-based systems.
• Familiarity with time-series analysis, uncertainty quantification, rare-event modeling, or reliability analysis.
• Experience supporting executive, regulatory, or external stakeholder decision-making.
• Experience in simulation evaluation, scenario coverage analysis, or safety-critical system verification.