Data Science intern (TikTok-Product-Data Science-Interaction-US) - 2025 Start (BS/MS) job opportunity at Tiktok.



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Tiktok Data Science intern (TikTok-Product-Data Science-Interaction-US) - 2025 Start (BS/MS)
Experience: 1-year
Pattern: full-time
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Salary:
Status:

Data Scientist

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loacation SAN JOSE, CA, United States Of America
loacation SAN JOSE, CA....United States Of America

Responsibilities Team Introduction TikTok-#Data #Science team is responsible for all data science and analytics related work, cooperating with all key value chains in TikTok, including User Growth, PGC, Content Ecosystem, Social, Creation, Product Infrastructure, Research and Science etc. The goal of the team is to generate actionable insights from data and help the stakeholders to make the right decisions. Our main tasks include metrics defining, root cause analysis, experimentation methodology, feature/strategy evaluation and exploratory analysis to find more opportunities. We are looking for talented individuals to join us for an #internship in 2025. Internships at TikTok aim to offer students industry exposure and hands-on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities at TikTok. Internships at TikTok aim to provide students with hands-on experience in developing fundamental skills and exploring potential career paths. A vibrant blend of social events and enriching development workshops will be available for you to explore. Here, you will utilize your knowledge in real-world scenarios while laying a strong foundation for personal and professional growth. 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 early. Responsibilities: Understanding user & item interests using statistical methods. Building user clustering and communities based on LLM labeling and understanding abilities. Coverting communities discovery results into algorithm strategy suggestions.

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