Content Safety & Top Spender Ops Project Intern (TikTok LIVE) - 2026 Start (BS/MS)

Responsibilities

Team Introduction
The LIVE Operations team is obsessed with everything to do with LIVE. From content strategy, monetization, gifting, LIVE features, data analysis, creating campaigns and ensuring a fun and safe space for all of our LIVE users.
We are looking for passionate and talented people to join the LIVE Operations team and support in our mission to inspire creativity and bring joy.

As a project intern, you will have the opportunity to engage in impactful short-term projects that provide you with a glimpse of professional real-world experience. You will gain practical skills through on-the-job learning in a fast-paced work environment and develop a deeper understanding of your career interests.
Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities:
- Own recurring updates, analysis, and root-cause identification for key regional content safety metrics; consolidate and interpret critical cases.
- Support top spender customer service operations, including handling daily inquiries, building and maintaining a Q&A knowledge base and intelligence repository, and coordinating with TPA vendors to ensure response timeliness.
- Draft promotional and communication copy for top spender-facing campaigns, and support cross-functional coordination across Global, regional, and creator-led campaign rhythms.
- Organize daily data for top spender diagnostic and root-cause analysis, produce weekly attribution reports, and provide ongoing information syncs to regional stakeholders.

Qualifications

Minimum Qualifications
- Currently enrolled in a bachelor's degree program or above.
- Strong interest in the livestreaming industry, content ecosystem, and platform safety governance.
- Able to commit at 3-4 working days per week with a minimum internship duration of 3 months.

Preferred Qualifications
- Prior experience in livestreaming, guild/MCN operations, creator ecosystems, or data analysis is preferred.