Autonomous Vehicle Safety Data Analyst

Torc Robotics, Inc.; Blacksburg (VA); Remote; USD 126,000 - 151,000; Full time

Benefits offered by this job

Bonus + stock options

Premium health benefits

401K with match

Paid vacation

AD+D and Life Insurance

Job summary

Torc Robotics, Inc. is a leader in autonomous driving software focused on automated trucks. The Safety Data Analysis team measures safety performance using engineering and statistical methods across on-road and simulation data sources.

The role develops indicators, automates workflows, and supports data-driven risk decisions. Candidates should have advanced degrees and strong Python/SQL skills, plus experience with large-scale time-series data and cloud-based analytics.

Qualifications

• Advanced degree in Data Science, Computer Science, Math, or a closely related field.
• Experience with Python and SQL.
• Experience with vehicle and sensor systems, cloud-based data technology, data visualization, and statistical analytics.
• Strong background in applied statistics, safety analysis, risk estimation, or decision support.
• Experience with large-scale time-series data and heterogeneous technical data sources.

Responsibilities

• Develop, implement, and refine safety performance indicators and targets.
• Apply statistically sound methods to evaluate safety performance.
• Develop automated analysis workflows for continuous safety monitoring.
• Ensure performance monitoring reflects real-world deployment and safety requirements.
• Communicate findings to diverse teams and stakeholders.
• Maintain documentation of methods, workflows, and outputs.

Skills

Python

SQL

Statistics

Data visualization

Agile methodologies

Problem solving

Communication

Time management

Education

B.S. in Computer Science or related field

M.S. in Data Science or related field

PhD in a related field

Tools

CI/CD

Cloud-based data tech

Job description

Torc Robotics, Inc. is a leader in autonomous driving software focused on automated trucks. The Safety Data Analysis team measures safety performance using engineering and statistical methods across on-road and simulation data sources.

The role develops indicators, automates workflows, and supports data-driven risk decisions. Candidates should have advanced degrees and strong Python/SQL skills, plus experience with large-scale time-series data and cloud-based analytics.