Data Labeling Analyst II (Contract)

The Data Labeling Analyst (DLA) will contribute to large projects and leverage analytical skills to help deliver lasting impact on Meta products. If you thrive in ambiguous environments and love finding areas for improvement, you've come to the right place. The main function of a DLA is to support and improve the quality of our labeling programs. DLAs support our project managers and partner with our global vendors to ensure all operational metrics meet targets. DLAs are expected to become Subject Matter Experts on labeling workflows and help deliver lasting impact for the product teams we support. Responsibilities: Become a subject matter expert in labeling workflows and labeling guidelines, practicing labeling in assigned queues to stay close to the workflow. Maintain relationships with vendor partners. Attend weekly business reviews and product team meetings and contribute to meetings regarding quality and/or technical barriers. Perform quality audits to provide labeling metrics and insights, support policy guideline updates, and recommend optimization opportunities across the labeling programs. Help vendors unblock obstacles by sharing data and escalating bugs and tooling issues to correct engineering teams with necessary documentation. Understand and help incorporate changes shared by cross functional partners to existing workflows, product features, and planned launches. Implement pre-approved changes to workflows and knowledge repositories. Help support and exchange knowledge with other PDO DLAs. • Create and modify data labels ensuring compliance to all regulatory, policy, and legal requirements. • Serve as the guideline/policy expert for the program and go-to SME for vendors and XFNs • Own weekly quality audit and golden set process • Own creation of weekly productivity and quality reports to XFNs • Oversee queue health and maintenance, maintain backlog, and troubleshoot bugs. • Communicate with vendor to deliver quality insights, updates to guidelines, and triage/answer program-related questions. • Label and analyze large data sets to gather insights on data quality.

At Meta, we are constantly iterating, solving problems, and working together to connect people all over the world. That's why it's important that our workforce reflects the diversity of the people we serve. Hiring people with different backgrounds and points of view helps us make better decisions, build better products, and create better experiences for everyone. We give people the power to build community and bring the world closer together. Our products empower more than 3 billion people around the world to share ideas, offer support, and make a difference.