Data Labelling Analyst - Trust and Safety Contract Position Job Description: The main function of a Data Labeling Analyst is to create and manage data labels while collaborating closely with our operations team to generate insights and optimise the labeling process. You will play a pivotal role in the development of AI and ML models, ensuring the accuracy and relevance across both integrity and support use cases. A key aspect of the role will involve identifying and addressing instances of bad actors or misrepresentation within data sets to uphold the integrity and authenticity of the content. While this role is not expected to engage with graphic content, there is a risk of some exposure. Good to have - Additional language Responsibilities: • Become an expert in various integrity and support issues across Operations. • Create and modify data labels, ensuring compliance with all regulatory and legal requirements. • Ensure the quality of labelled data sets, ensuring alignment with content policies and/or support processes. • Partner with team members to improve processes and tools of the team's labelling interfaces. • Deliver insights as appropriate related to observed trends in data labelling workflows. • Identify, investigate, and flag instances of bad actors or misrepresentation within data sets, ensuring compliance with standards for integrity and authenticity. • Collaborate with cross-functional teams (XFNs) to develop strategies for detecting and mitigating bad actor activity or content misrepresentation. Typical Day in the Role: • Policy reasoning rationing • Conducting review/investigation work for a specific tool - annotating on content • Set number of annotations to be confirmed • Working with (tech, integrity and product) • New technology, skills set critical thinking and strong language skills, articulate to Gen AI why its good and/or bad, language is key, have to be able to communicate effectively. Can collaborate with stakeholders, take insights and translate to technical teams. Required Qualifications: • Bachelor's degree or equivalent work experience in related field(s) (e.g. Computer Science, Information Systems, Intelligence Studies, Cybersecurity, Mathematics, Business Administration, etc.). • Professional experience in an office setting, working in an autonomous role. • Experience in data review and/or labelling processes. • Ability to identify trends within large data sets.