About the Team TikTok’s data scientist team is a critical component of the platform’s success, responsible for leveraging data to enhance user experience, optimize content delivery, and drive business decisions. As a leading social media app known for its short-form video content, TikTok relies heavily on data science to stay ahead in the market.
We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. 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 our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities：
- Conduct data analysis in LIVE related business, including watching experience, creator ecosystem, agency management, algorithm improvement and etc..
- Design metrics framework to measure product healthiness, keep tracking of core metrics and understand root causes of metric movements.
- Conduct scientific evaluation with statistical methods, including A/B testing and casual inference.
- Identify growth opportunities with data analytics, and drive business decisions. Work with PM/MLE/RD to deliver product and strategy improvement.
- Research data science theories and methodology, improve analysis efficiency and data product tools.
Minimum Qualifications:
- Individuals who are completing or have recently completed a Math/Computer/Machine Learning major.
- Expertise in SQL and programming in Python or R.
- Strong analytical and causal reasoning mindset, and rigidity on statistical correctness. Strong communication and passion about product challenges.
Preferred Qualifications:
- Experience of LIVE related business.
- Knowledge of machine learning and recommendation systems.
- Experience with big data technologies.