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Avride · 3 weeks ago

Data Quality Analyst

Austin, TX

Full-time

Onsite

Entry, Mid Level

Avride is looking for a Data Quality Analyst who will help improve and optimize their data annotation processes. The role involves working with lidar-based point cloud data, developing quality metrics, and ensuring consistent dataset quality across multiple workflows.

Artificial Intelligence (AI)AutomotiveAutonomous VehiclesRobotics

No H1B

Responsibilities

Design and automate metrics to evaluate annotation quality

Monitor these 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

Work closely with lidar-based 3D annotation outputs: review samples, spot issues, and provide structured feedback

Contribute to the design of 3D annotation pipelines

Perform recurring checks on edge cases and tricky scenarios to ensure consistency

Document edge cases and best practices for working with 3D data so that others can follow them

Regularly validate 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

Use Python and ClickHouse for analysis, monitoring, and process support

Work closely with product and engineering teams to implement improvements

Where possible, build scripts or LLM-based helpers to automate repetitive tasks — but be ready to handle the parts that still require manual attention

Qualification

PythonData Quality AnalysisLidar-based Data ProcessingClickHouseAnalytical Data StacksProcess-oriented MindsetSystems ThinkingAttention to Detail

Required

A degree in a relevant field (Computer Science, 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