Data Quality and Labeling Specialist

Location: Fully Remote

About the Opportunity: 

We are looking for a Data Quality and Labeling Specialist to join our machine learning team and play a critical role in acquiring and ensuring the accuracy, reliability, and integrity of datasets used to train our AI systems. 

From your first day, you will make a valuable — and valued — contribution. We are a fast-growing company where no one is a bystander. We offer you the opportunity to delight millions of consumers around the world while gaining meaningful experience across a variety of disciplines. 

Duties and Responsibilities: 

• Produce high-quality annotations for our AI, ensuring strict adherence to guidelines.
• Contribute to the development and implementation of data labeling quality assurance processes and procedures.
• Review and audit labeled data to assess accuracy and overall quality.
• Conduct regular quality assessments and generate reports for AI models running in production.
• Collaborate closely with project managers and AI scientists and engineers to align with project goals.
• Attend meetings to discuss and refine guidelines and best practices.
• Emphasize teamwork and effective collaboration.

Skills and Qualifications: 

• Strong reading comprehension skills and ability to interpret various types of content accurately.
• Strong critical thinking skills and ability to make sound judgments when dealing with complex datasets and labeling tasks.
• Previous data labeling or quality assurance experience will be considered favorably.
• Attention to detail and meticulous approach
• Independent and collaborative work style
• Effective communication and interpersonal skills

The following experience is a plus: 

• Experience in the news domain (fact checking, detecting misinformation etc.) and knowledge of journalistic principles highly desired. 
• Background or Interest in Political Science, Journalism, Artificial Intelligence (AI), Machine Learning (ML), Linguistics, or related domains will be advantageous.
• A background or keen interest in fields like Ethical AI, Fairness, Transparency, Explainability, Privacy, and related domains is advantageous