Applied Scientist

New
Remote US & CanadaFull-TimeMiddle
Salary not disclosed
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Job Details

Experience
Minimum of 3+ years of professional experience
Required Skills
PythonSQLProduct AnalyticsData science

Requirements

  • Minimum of 3+ years of professional experience in an analytical role (e.g., Data Science, Systems Evaluation, or Product Analytics).
  • BS/MS in a quantitative field such as Computer Science, Engineering, Statistics, Physics, or similar.
  • Strong command of SQL, and familiarity with Python for data manipulation and prototyping.
  • Experience building clear, automated dashboards using modern BI tools or custom frameworks.
  • Experience working with internal cross-functional partners/stakeholders
  • Open-minded and collaborative team player with willingness to help others
  • Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.
  • Experience in the Autonomous Vehicle or Robotics industry.
  • Experience with large scale databases and analytics
  • Practical understanding of statistical concepts (e.g., hypothesis testing, significance) as applied to real-world performance measurement

Responsibilities

  • Collaborate with cross-functional teams to provide comprehensive analysis on autonomy system performance across Waabi World (Simulation), Track, and Public Road testing.
  • Develop and maintain sophisticated, cross-modal dashboards that provide a unified and trustworthy view of the performance of our systems, tracking progress toward critical company milestones.
  • Partner with Data Platform and Evaluation teams to shape the evolution of eval tooling and pipelines, ensuring our infrastructure remains scalable, automated, and capable of validating complex system requirements across all testing modalities.
  • Act as a key partner to Safety and Autonomy teams, ensuring that our automated reporting faithfully captures the technical intent and requirements of our system KPIs.
  • Proactively monitor and investigate anomalies in metrics to ensure stakeholders are making decisions based on reliable, high-fidelity data.
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