Data Labeling Analyst II

Job Responsibilities:

Labeling / auditing a set amount of data daily, at the direction of Project Coordinators and Project Managers Reviewing and validating labeled datasets for accuracy and consistency. Performing QA in our in-house annotation tooling Flexing between projects as demand requires, adjusting to new project guidelines week-over week and learning multiple project guidelines at once Comprehending complex guidelines and product requirements to accurately label ML data to refine AI models Collaborating with team members to identify improvements to the labeling process to drive efficiency and promote high quality Supporting training new DLAs who join a project through shadowing sessions (i.e., letting other DLAs shadow their work) Operationalizing on Product feedback and bringing best data labeling practices downstream to peer DLAs in accordance with Product feedback and review Supporting with any additional tasks to help with program excellence Skills:

Required Skills:

Knowledge of foreign language preferred Machine Learning generalist background preferred Must pass our English annotation test KPIs:

Annotation quality (consistency, adherence to guidelines, etc.) Audit quality, precision, and accuracy Quality to speed / quality to throughput Accountability Engagement Education/Experience:

BA/BS required in STEM degree