Safety Data Analyst

At Torc Robotics, our Safety Data Analysis team sits at the core of how we measure, understand, and continuously assess the safety performance of Torc Drive. This team blends engineering, statistics, and large-scale data analysis to transform complex, multi-modal datasets into actionable safety insights.

Responsibilities

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

Requirements

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

Nice to have

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

Benefits

Competitive compensation package that includes a bonus component and stock options; 100% paid medical, dental, and vision premiums for full-time employees; 401K plan with a 6% employer match; Flexibility in schedule and generous paid vacation (available immediately after start date); AD+D and Life Insurance