Data Understanding - Team Lead - Malaysia

Responsibilities

About Data Cycling Center (DCC)

AI is the new electricity and data is the energy for AI. Our core belief is that unstructured data contains the untapped wisdom of humanity - and by building the best AI-ready data infrastructure, we enable more meaningful, responsible, and creative uses of AI.
Data Cycling Center (DCC) is a Data Science team that is responsible for building the mid-platform data layer that powers AI development across all business lines of TikTok, including e-commerce, advertising, livestreaming, and emerging technologies. Our initiatives include:
- Scaled human-in-the-loop (HITL) data processing (including capability, methodology, E2E process, platform), delivering the most cost-effective results at benchmark quality levels that outperform leading tech peers.
- Built a highly automated end-to-end data pipeline for AI-generated content (AIGC) that supports strong model performance with minimal resource input.
- Develop a comprehensive content understanding and insight generation system, setting new benchmarks for marketing intelligence in the online ads ecosystem.

DCC aims to be the number 1 data service provider in the AI era. Our mission is to build the most effective (lossless and affordable) content understanding capabilities to fully satisfy AI needs of TikTok and to help the industry push the limit.

The Team Leader will oversee a team of Data Understanding Specialists (DUS), providing hands-on guidance and support in operational execution and project delivery. This role focuses on day-to-day team management, ensuring that projects are delivered efficiently while maintaining high-quality standards. The ideal candidate will have experience in both operations and cross-functional project management, helping to bridge teams, drive progress, and support the professional growth of their direct reports.

Labelling rules clarification and training
- Define clear and unambiguous labelling rules to ensure high quality labelling output
- Simplify labelling rules to reduce contextual knowledge for labelling while providing training to labellers if needed
- Ensure that labelling rules meet model training requirements

Quality improvement and assurance
- Monitor and review quality of labelled data
- Timely root-cause identification of quality issues for remediation
- Identify opportunities and areas of improvement to optimize delivery

Project management
- Deliver projects on time and on target flagging any key risks that arise
- Deep dive into issues that arise during project lifecycle with solutions that ensure delivery
- Manage stakeholders to drive transparency across the data delivery pipeline

Leadership Skills
- Managing a team: ability to identify strengths and weaknesses, provide constructive feedback & motivate and recognize effort
- Building & Directing: encourage cross team collaboration, provide clear direction and milestones, inspire actions towards challenging objectives
- Ownership & Accountability: accept and apply constructive feedback, eager to embrace uncertainty, promotes culture and core values consistently

Why join us?
- Shape the Future of AI
Work at the core of TikTok's AI development, where your data powers cutting-edge applications across e-commerce, ads, livestream, and more.