Recommendation Product Manager Intern (TikTok-Product-Content Ecosystem) - 2027 Summer

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 us for an internship. Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth. Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals. Candidates may apply to a maximum of two positions across Our Company and its affiliates globally. Applications will be considered in the order they are submitted. Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates. Currently pursuing an Undergraduate/Master's in computer science, statistics, information management, data science or a related discipline.

Responsibilities: - Participate in the governance strategies for TikTok's content ecosystem and creators, and maintain a compliant, healthy, and high-quality global content ecosystem; - Responsible for the governance process of ecosystem issues, collaborate with the identification team to complete the design of recommendation strategies and governance paths, and focus on governing risks such as marketing accounts, low-quality accounts, and non-original content; - Support the iteration of governance strategies and experimental scheme design, propose optimization strategies based on content understanding and consumption data analysis, and collaborate with the algorithm and product teams for implementation; - Establish a mechanism-based monitoring system for the ecosystem health level, track the governance effectiveness, accumulate cases and data insights, and continuously improve the efficiency and outcomes of governance.