Staff Safety Data Scientist, Safety Analysis

Aurora Innovation Aurora Innovation · Robotics · PIT3 · Safety

Staff Safety Data Scientist role at Aurora Innovation focused on leading critical safety research for autonomous vehicles. The role involves applying advanced statistical and probabilistic modeling to analyze safety data, inform hardware/software decisions, and develop leading indicators for future performance. Responsibilities include developing quantitative data analytics, authoring technical analyses, designing data collection, and mentoring junior team members. Requires a strong background in risk and hazard assessment, data science techniques, and excellent communication skills.

What you'd actually do

  1. 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).
  2. Author and present technical analyses and findings to diverse internal and external audiences, including stakeholders, authoritative bodies, and industry forums.
  3. Design and automate data collection and analysis to support ongoing safety programs.
  4. 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.
  5. Develop statistical models and algorithms to predict potential risks and prevent incidents, improving the safety performance of autonomous systems.

Skills

Required

  • Python
  • SQL
  • R
  • statistical modeling
  • machine learning
  • predictive analytics
  • visualization software
  • leadership skills
  • communication and presentation skills

Nice to have

  • DBT
  • AWS
  • Autonomous Vehicles
  • Aerospace
  • Robotics

What the JD emphasized

  • safety related domain
  • safety principles and risk assessment methodologies
  • data science techniques to solve safety challenges and mitigate risks

Other signals

  • safety analysis
  • risk assessment
  • statistical modeling
  • probabilistic modeling
  • autonomous systems