Senior Data Scientist, Data Quality and AI Evaluation

What you'll do

• Define quality metrics and evaluation methods to assess auto-labeling pipeline performance and regressions.
• Build and maintain human-verified golden datasets covering representative driving conditions and critical corner cases.
• Analyze large-scale sensor and annotation data to identify root causes and systematic errors.
• Develop automated approaches for failure clustering and targeted data selection for human correction.
• Build statistically sound audits and experiments to establish release acceptance criteria.
• Communicate quality findings through clear dashboards and actionable recommendations for engineering teams.
• Partner with labeling operations to improve annotation guidelines and reviewer consistency.

What we're looking for

• 12+ years of industry experience.
• Bachelor degree or proven track record for Master in statistics, mathematics, computer science, engineering, or a related quantitative field.
• Great foundations in statistics, experimental design, sampling, hypothesis testing, and uncertainty estimation.
• Practical experience evaluating machine learning systems and data quality.
• Experience working on AI/LLM evaluation with proficiency in Python and SQL.
• Understanding of precision, recall, class imbalance, selection bias, data leakage, and evaluation across significant scenario groups.
• Strong communication and teamwork skills with experience working across engineering, research, product, or operations teams.
• Background with autonomous driving, robotics, or computer vision, particularly camera and LiDAR data (preferred).