Aurora's mission is to deliver the benefits of self-driving technology safely, quickly, and broadly. The Risk & Safety Data Science sub-team aims to generate insights and intelligence to safely and broadly commercialize autonomous vehicle technology by leveraging data to accelerate the development of the Aurora Driver, identifying key drivers of risk and informing critical decisions about our safety case.
Requirements
- 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 working with data transformation tools such as DBT
- Experience working on ETL pipelines and leveraging big data engines
- Experience using Amazon Web Services (AWS) tools
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
- 5+ years of industry experience as a Data Scientist, Analyst or similar technical role
- 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
- 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)
