Eco Governance Project Intern: Data-Driven Ops and Impact

TikTok Pte. Ltd.; Singapore; On-site; SGD 6,700 - 11,000; Part time

Job summary

TikTok Pte. Ltd. invites a Project Intern to contribute to Eco Governance within ADSO. You will support daily project operations, monitor labeling efficiency, and assist with resource allocation while coordinating with global partners. The role offers hands-on experience in a fast-paced setting.

Fluent Chinese and English are required, with strong coordination and time-management skills. This internship emphasizes learning, collaboration, and data-driven decision making in a dynamic environment.

Qualifications

• Pursuing an undergraduate degree in project management or a related discipline.
• Commitment of at least 6 months with a minimum of 4 working days per week.
• Ability to quickly understand business context and model training workflows.
• Proficiency in Chinese and English is required.

Responsibilities

• Support day-to-day project operations using internal platforms/tools for case injection and tracking labeling efficiency.
• Coordinate with cross-functional stakeholders to ensure consistent cadence and collaboration.
• Analyze project data to support data-driven decision making.
• Learn Content Ecosystem Governance policies and contribute to quality improvements.

Skills

Language proficiency English

Language proficiency Chinese

Coordination

Time management

Cross-functional collaboration

Data analysis basics

Education

Undergraduate degree in Project Management

Tools

SQL basics

Python scripting

Job description

TikTok Pte. Ltd. invites a Project Intern to contribute to Eco Governance within ADSO. You will support daily project operations, monitor labeling efficiency, and assist with resource allocation while coordinating with global partners. The role offers hands-on experience in a fast-paced setting.

Fluent Chinese and English are required, with strong coordination and time-management skills. This internship emphasizes learning, collaboration, and data-driven decision making in a dynamic environment.