TikTok's Content Ecosystem team is responsible for the health and prosperity of content users and creators to improve DAU in the long term.
Our team deeply dives into the following fields: tracking the whole content ecosystem and finding potential challenges and opportunities;
cooperating closely with the RD team on model recognition, content understanding, and algorithms, targeting to balance the traffic in different formats, optimize traffic distribution, content diversifications, creator experience of moderation, user experience of interactions, and more problems.
We are looking for talented individuals to join our team.
As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Successful candidates must be able to commit to an onboarding date by end of year. Please state your availability and graduation date clearly in your resume.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply.
The application limit is applicable to TikTok and its affiliates' jobs globally.
Applications will be reviewed on a rolling basis.
We encourage you to apply as early as possible.
Individuals who are completing or have recently completed a Bachelor's/ Master's degree in computer science, statistics, information management, data science or a related discipline.
Responsibilities:
- Follow content ecosystem trends closely, understand the balance between platform brand, content quality, and user experience, and participate in the development of content ecosystem governance policies;
- Contribute to the development and iteration of policy frameworks and guidelines;
analyze execution challenges and gaps in existing policies, propose optimization recommendations, and help ensure policy rationality and enforceability;
- Monitor and review key governance metrics, collect feedback from cross-functional partners, and provide data- and case-driven input for continuous policy improvement through issue analysis and case abstraction;
- Support the implementation and training of ecosystem policies, collaborate with labeling and strategy teams to improve execution consistency, track training effectiveness, and contribute to training program optimization.