TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Creation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.
Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.
To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always.
At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.
Join us.

As the window of TikTok's business services, our TikTok UED Monetization team aims to enable and inspire clients to effortlessly connect with audiences and maximize brand potential.

About The Tiktok Monetization Product Data Science Team
We're the TikTok Monetization Products data science team, who enables and champions data driven decision making. Our Vision is to become the world class data science team, where data is used rigorously to drive all decision making. Our Mission is to drive monetization and sustainable revenue growth for TikTok through data science.

Responsibilities:
1. Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
2. Build and manage high performance, responsive team of data scientists and analysts that are able to not only keep up with but also pioneer in this space
3. Build and prototype analysis pipelines for the team to provide insights at scale
4. Develop comprehensive knowledge of Tiktok data structures and metrics, advocating for changes where needed for product development
5. Develop deep partnerships with engineer and product teams to deliver on major cross-functional measurements, testing, and modeling efforts
6. Partner with Data Engineering to ensure the data accuracy and consistency