Labeling Specialist, DLO

Our Business Integrity team has a strong user focus and a dedication to technical excellence. We aim to meet our users’ needs with reliable and high-performing platforms and services. We are seeking a Labeling Specialist (English) to perform precise annotation and labeling of data, ensuring each task is paired with the correct label to provide essential ground truth for training machine learning models. This specialised role focuses on addressing complex tasks, extracting best practices, and driving continuous improvement in data accuracy. Success in this role requires exceptional attention to detail, a strong grasp of global policies, and the ability to consistently apply evolving guidelines to uphold the highest standards of data quality.

Responsibilities

• Accurately annotate and label data in line with global policy standards to support model development and performance.
• Stay abreast of all policy changes and/or developments to ensure accurate and consistent annotation and labeling operation.
• Adhere to defined policies and procedures while delivering high-quality results.
• Identify labeling challenges, suggest workflow/guideline enhancements to set a new benchmark.
• Support special projects and pilots aimed at improving data annotation quality, efficiency and scalability of labeling operation.
• Collaborate with cross-functional teams such as Training and Quality, Policy, etc. to enhance annotation workflows and ensure alignment with policy standards.

Requirements

Minimum Qualification(s)

• Proficiency in English is required
• Ability to work alternating work rotations and shifts (including public holidays and weekends)
• Diploma in any discipline from any Polytechnic
• Demonstrated computer proficiency with Microsoft Office
• Strong analytical and problem-solving skills with a keen attention to detail and process improvement.
• Highly organized, self-motivated, and able to work independently while collaborating effectively within a team.
• Proven ability to manage confidential information and perform effectively in fast-paced, high-volume, and diverse environments.