[Template] Engineeering

Avride•Austin, TX

55d•Onsite

About The Position

We are looking for a Data Quality Analyst who will help us improve and optimize our data annotation processes. In this role, you will work closely with lidar-based point cloud data, develop quality metrics, and ensure consistent dataset quality across multiple annotation workflows. You will be deeply involved in analyzing annotation outputs, identifying opportunities for process improvements, and implementing data-driven solutions. A key part of the role includes monitoring data quality, building validation mechanisms, and supporting the team with insights that help improve both the annotation pipeline and the final dataset. 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.

Requirements

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

Nice To Haves

Experience with ClickHouse
Strong systems thinking, attention to quality, and a proactive mindset.
Experience using semi-automated labeling tools or active learning methods.

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.