Data Quality Assurance Engineer, Marketplace Intelligence and Data (2027 Graduate)

Annotation Quality Pipeline Development:

• Collaborate with cross-functional teams to create and implement annotation quality pipelines that ensure consistent and accurate data labeling.
• Develop and refine quality control processes to identify and rectify issues in annotated datasets.

SOP Design and Documentation:

• Design, document, and communicate clear Standard Operating Procedures (SOPs) for data annotation teams.
• Train and educate annotation teams on SOPs to ensure adherence to quality standards.

Quality Evaluation:

• Conduct regular quality assessments of annotated data to identify discrepancies, inconsistencies, or errors.
• Collaborate with annotation teams to provide feedback and guidance for improving annotation quality.

• Bachelor's degree in a related field (e.g., Computer Science, Business Analysis, Information Management etc).
• Knowledge of machine learning and data labeling techniques.
• Knowledge of SQL, Python and Data Analysis skills is a plus.
• Ability to leverage AI tools to enhance day-to-day tasks and improve efficiency.
• Strong problem-solving skills with an attention to detail.