Staff Safety Data Scientist, Safety Analysis
- 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.
- 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.
- 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.
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