Senior Staff Safety Data Scientist

Who We Are

Aurora (Nasdaq: AUR) is delivering the benefits of self-driving technology safely, quickly, and broadly. Founded in 2017 by experts in the self-driving industry, Aurora is revolutionizing transportation – making it safer, increasingly accessible, and more reliable and efficient than ever before. Its flagship product, the Aurora Driver, is a platform that brings together software, hardware, and data services, to autonomously operate passenger vehicles, light commercial vehicles, and heavy-duty trucks. Aurora is partnered with industry leaders across the transportation ecosystem including Toyota, Volvo, PACCAR, Uber, Uber Freight, FedEx, and U.S. Xpress. Aurora tests its vehicles in the Bay Area, Pittsburgh, and Texas and has offices in those areas as well as in Bozeman, MT; Seattle, WA; Louisville, CO; and Detroit, MI. To learn more, visit www.aurora.tech.

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We’re searching for a Data Science Architect to lay the foundation in making data-informed decisions that impact the safety of  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.

In this role, you will

• 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

 Required Qualifications

• MS or PhD in Statistics, Mathematics, Applied Math,  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

 #LI-FF1

#Mid-Senior 

Working at Aurora

At Aurora, we bring together people with extraordinary talent and experience united by the strength of our values. We operate with integrity, set outrageous goals, and continue to build a culture where we win together—all without any jerks.

We have offices in 8+ locations across the United States. We offer a competitive benefits package to qualifying employees. Our Career Page includes everything you need to know about working at Aurora.

At the core of everything we do is our commitment to safety. Building best-in-class self-driving technology will take time, and we believe that each employee at Aurora has a role in contributing to safety, every step of the way. Aurora expects commitment to our safety policies from every employee, and seeks candidates who take an active responsibility, can contribute to building an atmosphere of trust, and invest in the organization’s long-term success by prioritizing working safely, no matter what.

We believe that self-driving technology has broad benefits – including an increase in safety and access to transportation – and to achieve those benefits, we want and need a workforce with diverse experiences, insights, and perspectives; said another way, a workforce that reflects the communities and people our technology will benefit. You can find all the latest news on our Blog

Individuals seeking employment at Aurora are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, pregnancy status, parent or caregiver status, ancestry, political affiliation, veteran and/or military status, physical or mental disability, or any other status protected by federal or state law. 

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