Data Quality Analyst- Autonomous Vehicles

Data Quality Analyst
- Autonomous Vehicles

Austin, Texas

Our autonomous vehicles encounter a wide variety of real-world situations on city streets. These situations need to be identified, categorized, and described in a structured way so they can be analyzed and used to evaluate the quality of our technology.

We are looking for a Data Quality Analyst who will help us validate and analyze real-world data related to the situations our autonomous vehicles encounter every day. In this role, you will work closely with production, develop quality metrics, and ensure consistent dataset quality across multiple annotation workflows.

You will be involved in the analysis and validation cycle: understanding test cases, working with collected data, validating its quality and completeness, analyzing results, identifying behavioral issues and coverage gaps, and determining where additional testing or investigation may be needed.

This is a data-focused role. You will work primarily with already collected data, test results, and driving scenarios, using analytical tools to understand vehicle behavior and support the testing and engineering teams.

This position is ideal for someone who is detail-oriented, comfortable working with complex datasets, and motivated to enhance data quality and annotation efficiency through analytical and technical approaches.

Data Analytics

• Analyze individual samples of data in detail to understand what happened and which factors may have affected situation;
• Identify edge cases and scenarios that require additional investigation;
• Monitor quality metrics on a regular basis and investigate anomalies;
• Analyze dataset balance and completeness across locations, scenarios, and labels;
• Assess how new scenes contribute not just more data, but better data.

Operational Routine & Controls

• Regularly reviewing annotation batches (including repetitive checks) to make sure they meet quality and coverage expectations;
• Maintain simple control dashboards and reports, update them on a weekly basis, and follow up on issues;
• Take care of many small but important operational tasks that keep the annotation process stable and predictable.

Support & Automation

• Use Python and Click House for analysis, monitoring, and process support;
• Work closely with product and engineering teams to implement improvements;
• Automate data validation, test-result processing, coverage analysis, and repetitive investigation workflows.

• A degree in a relevant field (Computer Science, Quality assurance, Data Analytics, Engineering, or another technical discipline);
• Strong analytical thinking and attention to detail — you’ll frequently review data, spot anomalies, and work through repetitive validation tasks;
• Practical Python skills for data processing and analysis (Pandas);
• Ability to query databases and work with analytical data stacks;
• Readiness to handle routine and sometimes monotonous work — dataset checks, manual validations, and weekly quality reviews are a core part of the role;
• A process-oriented mindset: ability to follow existing workflows, maintain consistency, and keep documentation and reports up to date;
• A valid driver's license and practical driving experience.

• Experience with Click House
• Experience with QA, testing, or validation workflows;
• Strong systems thinking, attention to quality, and a proactive mindset.
• Experience using semi-automated labeling tools or active learning methods.

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Candidates are required to be authorized to work in the U.S. The employer is not offering relocation, sponsorship, and remote work options are not available.

Avride is an equal opportunity employer and committed to providing reasonable accommodations to qualified applicants and employees with disabilities to ensure they have equal access to employment opportunities. Avride complies with the Americans with Disabilities Act (ADA), if you need a reasonable accommodation to assist with the application or hiring process, or to perform the essential functions of a job, please email jobs.