Aurora delivers the benefits of self-driving technology safely, quickly, and broadly.
Pittsburgh, PA, US
Bringing self-driving vehicles to our roads is the most transformative opportunity of our generation. Aurora is taking a fresh start with the development of self-driving technology, combining excellence in AI, rigorous engineering, and a team with decades of experience building robots that work.
Led by a team of seasoned experts, our mission is to deliver the benefits of self-driving technology safely, quickly, and broadly. We are designing the software and hardware to power the transportation of our future that will make our roads safer, give more people access to mobility, and reduce congestion and pollution in cities - improving the quality of life for all. The challenge in what we are endeavoring to achieve is transcendent; we are developing perhaps the world's most complex computing system and asking it to perform the task of transporting and keeping safe our most precious asset: human life.
Aurora hires people who want to build the future of transportation. We are looking for our Data Science Architect to lay the foundation in making data-informed decisions that impact the Autonomous Vehicle behaviors, verification and validation of Aurora's self-driving technology and business growth. While interviewing, you will be expected to intelligently reason about various applications of data science in the verification and validation of autonomous driving which include heuristics that define safe driving behavior, data adequacy requirements to address sample size issues, and data quality issues. Your role will interface with Product, Autonomy Development, Systems and Safety Engineering teams and will drive mission-critical decisions in a multi-trillion dollar industry.
- Define safety risk framework/architecture to quantify system and subsystem risk
- Define heuristic models and data requirements to establish statistical arguments for good driving behaviors
- Identify key metrics for safety and performance of autonomous driving in selected Operational Design Domains (ODDs), based on first principles, as well as an analysis of manual and autonomous driving miles
- Establish human driving performance and safety baselines in selected ODDs
- Define data-driven targets for autonomous driving performance and safety in selected ODDs. Be able to argue for why those targets are valid and reason about the effect on traffic safety if those targets are achieved
- Guide the design of Simulated and real-world driving experiments to efficiently understand the gaps between achieved system performance/safety and desired targets
- Assist with methodologies and planning for AV verification and validation at system and subsystem level
- Support the development of market entry plans that align market opportunity with technical capability
- Support and educate other technical teams on their data science needs
- Identify, utilize, or create as appropriate the needed technical machinery for large scale data analysis and visualization. In particular, to analyze historical and current data and use it to predict future system performance
- Discover and analyze relevant information from multiple large data sets to further Aurora's mission of delivering Autonomous Vehicle technology Safely, Quickly and Broadly
- Work with Motion Planning, Perception, Safety and Simulation engineers to ensure their respective teams have the information they need to make timely, informed decisions.
- Surface succinct, actionable data widely in regularly updated dashboards
- MS or PhD in Statistics, or a related field.
- Experience architecting data and software systems to facilitate reliable statistical analysis at scale
- Practical knowledge of common data analysis, inference, and statistical modeling tools, including Python and/or R
- Self-starter who will see opportunities to apply capabilities that add value throughout the organization
- Superb analytical and problem solving skills, and an ability to deeply understand the “why” and “how” of what we are working on
- Strong interpersonal and communication skills
- Excellent planning and organizational abilities
- Ability to technical leadership and mentoring
- Enthusiasm for applying data science to the toughest challenges in autonomous driving
- 6+ years of experience in a Data Science/Statistical Analysis role is preferred
Working at Aurora
Our work has real purpose. Delivering self-driving will improve lives around the world, expanding access to transportation, revitalizing cities, giving people more time back every day.
We’re one team. We’re inspired by the challenge of what we’re solving and the impact our work will have on society. Our camaraderie is built on respect for our work and the fundamental belief our success will be a result of working together.
The Founding Team
Aurora has assembled the most experienced leadership team in the space. Chris Urmson helped lead Carnegie Mellon’s efforts in Darpa’s Grand Challenges, then was a founding member of Google’s self-driving team. Sterling Anderson worked on the tech at MIT before leading Tesla’s Autopilot system. Drew Bagnell, also a Carnegie Mellon alum, is a machine learning expert who helped build Uber’s autonomy effort. At Aurora, these three continue to bring experts from all areas of the industry to the team. We are funded by Amazon, T Rowe Price, and some of Silicon Valley’s best venture capital firms, including Sequoia, Greylock and Index Ventures.