Data Quality Analyst - Data Annotation, ML Data Quality, MAP Annotation

About the Position

The Data Quality Analyst is a critical role within the organization, responsible for ensuring the integrity and accuracy of data utilized in artificial intelligence applications. This position involves overseeing data annotation processes across various projects while maintaining compliance with established quality standards.

Accountabilities

• Oversee and coordinate data annotation projects, ensuring all work adheres to defined quality benchmarks and timelines.
• Conduct comprehensive quality audits on annotated datasets to guarantee alignment with project specifications.
• Analyze data quality issues through root cause analysis (RCA) and execute corrective actions to enhance overall data quality.
• Collaborate with cross-departmental teams to refine data quality workflows and implement process improvements.
• Mentor team members on best practices related to data annotation and quality assurance methodologies.
• Implement 2D and 3D annotation techniques to optimize datasets for machine learning model development.

Skills and Experience Required

• Proficiency in various data annotation techniques and associated tools.
• In-depth knowledge of machine learning data quality principles and standards.
• Experience with map annotation methodologies and effective quality auditing processes.
• Strong analytical abilities with a focus on problem-solving, particularly in relation to root cause analysis.
• Proven experience in managing teams and leading project initiatives effectively.
• Familiarity with industry standards regarding AI data quality assurance.

Suitably qualified candidates are invited to submit their applications for this pivotal role in enhancing data quality within our organization.