Aurora's mission is to deliver the benefits of self-driving technology safely, quickly, and broadly. The Aurora Driver aims to create a new era in mobility and logistics, bringing a safer, more efficient, and more accessible future to everyone. The Risk & Safety Data Science sub-team is focused on generating insights and intelligence to help safely and broadly commercialize autonomous vehicle technology.
Requirements
- 5+ years of industry experience as a Data Scientist, Analyst or similar technical role
- Demonstrable expertise in coding, programming concepts, and technical tools, combined with the enthusiasm and passion to build. Must be expert at using Python
- Advanced knowledge and experience using relational databases (SQL, PostgreSQL, etc.) and knowledge of best practices for Data Engineering
- Strong understanding of both common and advanced Data Science modeling tools and technologies (eg. numpy, sklearn, pytorch, etc.)
- Experience driving Data Science analysis end-to-end, working closely with Engineering and Product to productionize pipelines, surfacing insights scalably
- Experience driving cross functional alignment across major technical programs
- Proven ability to communicate technical, data-driven analysis to both technical and non-technical audiences across stakeholders, including translating and cascading Executive input into their work
Responsibilities
- Lead the design and development of rigorous metrics, models, and statistical analyses to assess and continuously improve the safety performance of the Aurora Driver.
- Conduct in-depth analyses of on-road and simulated data to identify and characterize safety events and risks.
- Develop data-driven probabilistic models to evaluate the safety of the product and support risk-based decision-making.
- Partner with engineering teams to develop and maintain Safety Performance Indicators (SPIs) and contribute to critical verification and validation (V&V) work products.
- Serve as a technical expert for the team, providing guidance and mentorship to junior data scientists and analysts.
- Champion data science best practices, including code reviews, data governance, and scalable data workflows.
- Present complex technical findings and data-driven recommendations to both technical and non-technical stakeholders.
Other
- Experience in a safety-critical industry (e.g., autonomous vehicles, aerospace, robotics, medical devices) and a strong understanding of safety engineering principles and risk assessment methodologies.
- Familiarity with functional safety standards and regulations (e.g., ISO 26262, UL 4600)
- Knowledge of safety-related data analysis, including a track record of using data to inform safety cases or support regulatory compliance.
- Advanced degree (MS or PhD) in Statistics, Computer Science, Operations Research, Economics, or a related quantitative field
- Experience working with data transformation tools such as DBT
