Buyers Edge Platform is looking to ensure the accuracy and reliability of their AI-based systems, data pipelines, and automation processes by hiring a QA Analyst.
Requirements
- Proficiency in SQL for investigating data integrity, creating reports, and validating data logic.
- Hands-on experience with manual and exploratory testing in data-centric or model-driven environments.
- Experience validating or curating training datasets, tagging systems, or model classification outputs.
- Familiarity with evaluation metrics such as precision, recall, accuracy, and confidence scores.
- Exposure to model auditing, structured output validation, or annotation workflows.
- Understanding of RESTful APIs and structured response formats (e.g., JSON, YAML).
- Basic scripting experience (Python, shell, etc.) for test automation or data manipulation.
Responsibilities
- Conduct QA and validation on outputs from AI models, data pipelines, and automation workflows.
- Identify and document errors, inconsistencies, and anomalies in largescale datasets or model-generated outputs.
- Develop and maintain SQL-based validation scripts and reports to track data integrity across systems.
- Perform manual and exploratory testing of AI features, classification systems, and automation logic.
- Create clear documentation and QA reports that describe findings, reproducible test cases, and impact assessments.
- Support continuous improvement of model evaluation frameworks and QA processes.
- Participate in cross-functional reviews to ensure AI systems meet quality and performance standards prior to deployment.
Other
- 2+ years of experience in QA, data analytics, or testing roles focused on data quality or AI output validation.
- Strong ability to analyze and interpret large datasets or AI-generated outputs to identify issues and trends.
- Excellent analytical, classification, and documentation skills—able to articulate nuanced findings beyond pass/fail results.
- Highly organized with the ability to manage multiple concurrent QA cycles.
- Naturally curious and detail-oriented, with the confidence to question assumptions and surface data-driven insights.
