(US) QA Auditor (Sampling, Quality Gates, Release Readiness)

Role goal: Protect dataset quality at scale by running sampling-based audits, enforcing quality gates, and ensuring every dataset release is audit-ready and meets acceptance thresholds.

Execute sampling plans (stratified by label type, difficulty, site/surgeon/device, model confidence) for ongoing QA and release audits.

Audit annotations against guidelines + ontology; score defects using standardized rubrics (severity, type, root cause).

completeness/coverage checks

schema/constraint checks (illegal combinations, temporal consistency, boundary rules)

defect density and rework thresholds

Generate rework tickets with precise instructions; track closure and verify fixes.

Partner with Annotation Lead to drive calibration actions (training refreshers, guideline clarifications, examples library).

Maintain QA dashboards: defect rate, rework %, gate pass rate, audit cycle time, top error patterns by annotator/team/label type.

Support release readiness: ensure required artifacts are complete for the Evidence Pack (QA results, sampling logs, sign-offs).

Escalate systematic issues to Adjudication/Clinical Review (definition gaps, ambiguous classes, recurring edge cases).

Deliverables (what you produce weekly)

QA audit reports (sample size, findings, severity distribution, root-cause categories)

Gate status + release checklist sign-off recommendations

Rework queue and closure verification

Trend insights and corrective action plan (top 3 issues + fixes)

3–7+ years in data QA / annotation QA / operations quality; experience auditing labeled datasets (video preferred).

Strong command of sampling-based QA: stratified sampling, acceptance thresholds, and audit scoring.

High attention to detail; comfortable reading and enforcing detailed SOPs/guidelines.

Strong documentation skills; can write clear defect descriptions and rework instructions.

Comfortable with dashboards/spreadsheets; basic metric literacy (defect density, rework, throughput).