Data Scientist, Analytics - Tiktok

TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Singapore, Jakarta, Seoul and Tokyo.

Why Join Us
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.

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.

The primary role of a Data Scientist for our Data team is to conduct deep analysis into user behavior, product features and content ecosystem to generate business insights that could be applied to actionable improving initiatives. You will work closely with cross-function teams, such as Product Management, Research and Development, Machine Learning Engineering, to improve user experience and fulfill growth of TikTok in all different regions.

Responsibilities - What You'II Do
- Work with large and complex data to solve technical and statistical challenges, and drive business impact.
- Design metrics framework to measure product healthiness, keep tracking of core metrics and understand root causes of metric movements.
- Drive data informed decisions on experiment launches and rigorously measure the impact of product or technical changes.
- Validate hypotheses, identify product growth opportunities, and influence direction for improvement with analyses, experimentation or other scientific methods.
- Partner with engineers and product stakeholders to deliver product insights and strategy.