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Open nowPosted 30 hours ago

Data Product Project Intern (TikTok Platform Responsibility) - 2026 Start

TikTok4,294 open roles

Where
Singapore
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Your applicationOpen nowData Product Project Intern (TikTok Platform Responsibility) - 2026 StartTikTok · Singapore
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The clock on this job

Early applications get read.

13.4% of postings close within 7 days. Measured by our own scanner across the market. TikTok postings stay open a median of 25 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.6%3 days
  3. 13.4%7 days
  4. 21.6%14 days
  5. 36.2%30 days
  6. 59.0%60 days
This job: posted 30 hours ago

TikTok median: 25 days open

The posting

About the Team The Platform Responsibility team is bringing disruptive innovation to content safety through the deep application of AI. We are building next-generation infrastructure that leverages advanced LLMs to reshape risk detection and governance. By engineering high-quality data pipelines and integrating AI into core decision-making, we drive exponential efficiency gains and precision. Working at the intersection of scalable engineering and technology, we empower global business growth while serving as the foundation of user trust.

About the Role This role will mainly support product management of our cluster and policy libraries, working with the teams that use them to make the libraries more consistent and useful. It will also support some data management, including documenting the database schema, helping optimise the data pipeline and organising its implementation.

As a Project Intern, you will contribute to impactful short-term projects and gain hands-on experience in a fast-paced, professional environment. This internship offers the opportunity to develop practical skills, apply your knowledge to real-world challenges, and explore your career interests. Applications are reviewed on a rolling basis, so we encourage you to apply early.

Responsibilities: Library Product Management - Standards and Definitions: Help set naming rules, definitions and quality checks for the cluster and policy libraries. Write them up clearly so that they can be applied consistently across teams. - User Feedback: Gather needs and feedback from the teams that use the libraries. Identify recurring issues and summarise them into clear recommendations for improvement. - Adoption: Help teams adopt new standards and library changes through written guidance and walkthroughs. Follow up on how the changes are being used, and flag blockers early.

Data Management - Schema Documentation: Document the expected database schema, including tables, fields, keys and how records relate, so that the team can build to one agreed design. Keep the documentation up to date as the design changes. - Pipeline Improvement and Implementation: Help draft ways to optimise the data pipeline, including how ground-truth results are kept up to date in the database, so that the data stays accurate. Work with the team to implement agreed changes and track progress.

Minimum Qualification(s) - Currently pursuing a Bachelor's degree. - Experience in product management, project coordination or a similar role through an internship, coursework or a student organisation, including working with several stakeholders to move a project forward. - Strong written and verbal communication skills. Able to turn rough ideas into clear standards and documentation that different audiences can follow. - Understanding of database concepts such as tables, fields, keys and relationships between tables. Able to read and document a database schema. - Strong problem-solving skills. Able to break down an ambiguous problem, prioritise what matters, and turn it into a plan with clear next steps. - Fluent in English and Mandarin. Proficiency in Mandarin is required primarily to facilitate coordination and communication with Chinese counterpart partners. - Able to start as soon as possible and intern for at least 6 months, 3 days a week, in Singapore.

Preferred Qualification(s) - Internship experience in product management, such as gathering user feedback or writing guidance. - Experience setting up a taxonomy, data dictionary or similar shared set of definitions. - Exposure to data pipeline or ETL concepts such as ingestion, transformation and loading.

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