Staff Safety Data Scientist, Safety Analysis

Who we are Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly. The Aurora Driver will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone. At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit aurora.tech or follow us on LinkedIn . We are searching for a Staff Safety Data Scientist on the Safety Analysis team who is a technical leader and go-to expert for risk and safety guidance, leveraging deep expertise in data science to lead critical safety research. Your insights will drive the safety strategy and external safety communications, including the development of industry-leading, benchmark safety studies and frameworks. The role requires a strong background in risk and hazard assessment and exceptional communication and interpersonal skills. You will be responsible for applying advanced statistical analysis and probabilistic modeling to support the safety case, inform hardware and software decisions, and identify critical risk factors. You will collaborate with diverse stakeholders across engineering, operations, and product. In This Role, You Will: Lead the development of novel quantitative data analytics using both proprietary (Aurora-logged, sensor, system, integration testing data) and publicly available data (CRSS, FARS, state-level information). Author and present technical analyses and findings to diverse internal and external audiences, including stakeholders, authoritative bodies, and industry forums. Design and automate data collection and analysis to support ongoing safety programs. Extract insights from historical system safety performance to develop leading indicators for future performance forecasting. Analyze safety data from operational vehicles, crash metrics, and near-miss incidents to inform safety strategies and decision-making. Develop statistical models and algorithms to predict potential risks and prevent incidents, improving the safety performance of autonomous systems. Model self-driving vehicle behaviors at the system and subsystem levels. Develop and maintain reports and expressions of baseline risk coverage and application in operations. Design and develop expressions of risk benchmarking from similar industries. Create dashboards and reports for communicating risk, ranking, and anomalies. Present safety research findings to senior leadership and recommend actionable improvements to safety protocols and operational systems. Mentor and lead junior team members, fostering their professional growth. Required Qualifications Bachelor’s degree in Data Science, Statistics, Mathematics, Physics, Engineering, Computer Science, or equivalent applicable technical experience. 7+ years of progressive experience solving large-scale complex problems. Demonstrated experience in a safety related domain (e.g., transportation, aerospace, robotics, medical devices). Strong understanding of safety principles and risk assessment methodologies; with a proven track record of using data science techniques to solve safety challenges and mitigate risks in a dynamic environment. Deep command of statistical methods, probabilistic modeling, and performing rapid exploratory data analysis. Expertise in data science tools (e.g., Python, SQL, R), statistical modeling, machine learning, predictive analytics, and visualization software (e.g., Tableau, Power BI). Adept at querying, analyzing, and visualizing large datasets. Excellent communication and presentation skills, with the ability to convey complex information to various audiences. Strong leadership skills, with the ability to provide guidance and mentorship. Ability to work independently, as part of a cross-functional team, or as a project lead. Desirable Qualifications Advanced degree in Statistics, Mathematic