This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
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.
Job Responsibility:
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
Requirements:
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
Nice to have:
Advanced degree in Statistics, Mathematics, Physics, Engineering, Computer Science, or equivalent applicable technical experience
Experience working in safety and risk, ideally complemented by a portfolio of publications, reports, or conference presentations
Familiarity with rapidly scaling operational environments
Proficient in working with advanced data transformation tools such as DBT
Skilled in building and deploying using Amazon Web Services (AWS) tools
Background in the Autonomous Vehicles, Aerospace, or Robotics domains