Enhancing the shopping experience and reducing logistics operational costs at TikTok's E-commerce Global Supply Chain and Logistics team
Requirements
- Experience in machine learning and statistics, familiar with the principles and model structures of common machine learning and deep learning algorithms for classification, regression, and clustering, with practical application experience;
- Experience in programming languages such as Python/Java, possessing excellent coding abilities, and familiar with at least one common machine learning/deep learning framework (TensorFlow/PyTorch etc.)
- Currently pursuing a PhD degree in fields such as artificial intelligence, computer science, operations research, automation, statistics, mathematics, or related disciplines, with experience in data mining and deep learning;
- Published papers at conferences such as KDD, NeurIPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RecSys, or having participated in data mining/machine learning competitions.
- Internship experience or research experience, especially in e-commerce, supply chain, logistics, and transportation;
Responsibilities
- Responsible for the development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business;
- Utilize e-commerce big data and deep learning models to predict end-to-end estimated time of arrival (ETA), and some logistics events such as failed delivery, delivered but not received to enhance the user logistics experience.
- Utilize time series forecasting techniques to predict sales at different granularities and horizons, such as warehouse-level manpower forecasting, inventory-level demand forecasting etc.
- Participate in the growth of e-commerce merchants/creators, responsible for the growth algorithm of e-commerce merchants/creators, including potential merchants/creators mining algorithm, tiering algorithm, out-reach algorithm, growth algorithm, etc.
- Combined with massive e-commerce information, through data mining and machine learning, predict the performance of products in traffic/conversion, improve the efficiency of product operation strategy and pricing/subsidy strategy, and assist in optimizing traffic distribution, to satisfy the requirements of product growth, cost optimization and some other scenarios.
Other
- Currently pursuing a PhD degree
- Graduating December 2025 onwards with intent to return to degree-program after the completion of the internship;
- Demonstrated software engineering experience from previous internship, work experience, coding competitions, or publications;
- Ability to state availability clearly in resume (Start date, End date)
- Acceptance of global applicant privacy policy
