Data Science Intern (TikTok LIVE) - 2027 Summer

About the Team:

Tik Tok Live Data Science team is responsible for Live growth, ecosystem and revenue strategy analytical work. We work closely with Algorithm team and Product team. The goal of the team is to generate actionable insights from data, driving Live to create an environment that brings communities together in real time to create meaningful and interactive connections around the globe. Our main tasks include metrics defining, root cause analysis, experimentation methodology, strategy evaluation and exploratory analysis to find more opportunities.
Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals.

Candidates may apply to a maximum of two positions across Our Company and its affiliates globally. Applications will be considered in the order they are submitted.

Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates.

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.

Requirements:

• Minimum Qualifications

• Individuals who are completing or have recently completed a Bachelor's/ Master's degree in Data Science or a related discipline.

• Expertise in SQL

• 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 programming with Python or R.