Data Annotation Specialist - TikTok PDPO (Singapore)

TikTok
Singapore
Full time
3 weeks ago
TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us
Creation is the core of TikTok's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. To us, every challenge, no matter how ambiguous, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At TikTok, we create together and grow together. That's how we drive impact-for ourselves, our company, and the users we serve. Join us.

About the Team
PDPO(Privacy and Data Protection Office) is the organization to lead, supervise, and empower all TikTok's privacy work in an accountable and industry leading way. This team is the expert in the landscape of privacy risks and passionate about consulting across the company on implementing the proper safeguards and technical mitigations to ensure that our users’ privacy is honored across the TikTok's products and platforms.

Job Responsibilities:
1. Support data classification and taxonomy methods and standards, understand business, cooperate with data team. Support analysis, identification and marking various data samples in storage, and ensure accuracy and recall rate.
2. Support AI team to improve algorithm recognition and machine learning ability, analyze badcase of algorithm recommended data labels, put forward suggestions and basis for annotation/labelling, and participate in the discussion of algorithm model improvement solutions
3. Deeply understand the business, investigate the data samples of each business line, and improve the classification standard of data labels and sample database
4. Improve the data annotation operation process, optimize the label sampling and review mechanism, and improve the efficiency of manual or automated standards
5. Participate in the functional optimization design of the annotation platform
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