Logistics Risk Data Analyst Project Intern (TikTok Shop) - 2026 Start

Responsibilities

About the Team
TikTok Shop's Governance and Experience (GNE) is a global team responsible for ensuring our marketplace is safe and trustworthy for not only our users, but also sellers and creators. We value user satisfaction and work on policies, rules, and systems to ensure quality. Our mission is to provide world-class service and experience for customers, sellers, and creators.

Role Overview
TikTok Shop is TikTok's global e-commerce platform that connects consumers, creators, and merchants across the world through immersive content experiences.
Our Singapore-based Logistics Risk team safeguards the integrity of TikTok Shop's global logistics ecosystem, supporting key markets across the US and EMEA. We leverage large-scale data analytics, risk intelligence, and AI technologies to detect emerging logistics fraud, optimize risk strategies, and minimize platform financial losses while ensuring a secure and trustworthy fulfillment experience.

As a Logistics Risk Data Analytics Intern, you will work closely with Risk Strategists, Product Managers, Data Scientists, and Engineers to analyze complex logistics data, uncover fraud patterns, and develop data-driven risk solutions. This role offers hands-on experience across the full lifecycle of logistics risk management-from risk investigation and strategy development to performance evaluation and cross-functional implementation.

As a Project Intern, you will contribute to impactful short-term projects and gain hands-on experience in a fast-paced, professional environment. This internship offers the opportunity to develop practical skills, apply your knowledge to real-world challenges, and explore your career interests.
Applications are reviewed on a rolling basis, so we encourage you to apply early.

Job Responsibilities
1. Data Exploration & Risk Signal Mining
- Analyze large-scale carrier, order, and merchant data to identify abnormal patterns and uncover emerging logistics fraud signals. Transform complex datasets into actionable insights that support risk detection and strategy development.
2. Risk Investigation & Root Cause Analysis
- Conduct in-depth investigations into logistics risk scenarios, including fake tracking, postage fraud, and compensation abuse. Summarize fraud patterns and support the continuous evolution of risk strategies.
3. Strategy Analysis & Performance Evaluation
- Monitor key logistics risk metrics and evaluate the effectiveness of existing risk control strategies through data analysis. Identify coverage gaps and recommend optimization opportunities to improve recall, precision, and operational efficiency.
4. Cross-functional Collaboration
- Partner with Risk Strategy, Platform Product, Engineering, Data Science, and Algorithm teams to support strategy implementation, experiment analysis, and data-driven decision making.
5. AI & Risk Innovation
- Explore the application of Large Language Models (LLMs) and AI tools to improve fraud investigation, knowledge management, and analytical efficiency across logistics risk scenarios.

What You'll Gain
- Gain hands-on experience solving real-world logistics fraud and risk problems on a global scale.
- Work with cutting-edge technologies including AI, LLMs, and large-scale data analytics.
- Receive mentorship from experienced logistics risk strategists and participate in the full lifecycle of risk strategy development.
- Develop strong cross-functional collaboration skills by working with global teams.

Qualifications

Minimum Qualification(s):
- Currently pursuing a Bachelor's or above degree in Data Science, Statistics, Mathematics, Computer Science, Information Systems, Supply Chain, Logistics, or related disciplines.
- Strong SQL skills with the ability to independently extract, clean, and analyze large datasets.
- Familiarity with Python (Pandas, NumPy, etc.) or R for data analysis.

Preferred Qualification(s):
- Strong analytical thinking, structured problem-solving ability, and attention to detail.
- Self-motivated, curious, and eager to learn in a fast-paced environment.

If you have any questions, please reach out to us at apac-earlycareers@tiktok.com