TikTok will be prioritizing applicants who have a current right to work in Singapore, and do not require TikTok's sponsorship of a visa.

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.

About the Team
The E-commerce Global Supply Chain and Logistics team is dedicated to enhancing clients' shopping experience and reducing logistics operational cost in TikTok E-commerce. We are currently looking for talented software engineers that have a deep understanding of machine learning (ML), operations research (OR), data mining and statistical inference. This position can be fulfilled in our Singapore offices.

Responsibilities
- Build deep learning and statistical models to provide end-to-end estimated time of arrival (ETA) prediction for the e-commerce logistics. Through fine adjustment of ETA expression to the consumers, improve the click-to-order rate while balancing the negative review indicators.
- Use data mining tools to build logistics network knowledge graphs, based on which to construct a situational awareness & early warning system for logistics fulfillment, enabling operations to discover and deal with logistics network anomalies, and to improve the logistics fulfillment quality together with logistics service providers.
- Analyze and predict the spatio-temporal trajectory sequence of express packages through deep learning, statistical inference and other algorithmic methods. This trajectory prediction can help to build a better understanding of logistics network dynamics, improve ETA prediction accuracy and provide important sample features for other prediction tasks.
- Build a service network design (SND) model for the location selection of transshipment centers and last mile stations based on an expected increase in logistics order volume.
- Collaborate with stakeholders to design and iterate strategies and models for predicting logistics events at the order level, including false shipments, user complaints, failed deliveries, false dispatching, negative reviews, and more.
- Drive the implementation of algorithmic models and ensure they generate tangible business value, such as logistics cost savings, GMV (Gross Merchandise Value) growth, and improved service levels.
- Develop innovative and state-of-the-art e-commerce logistics models and algorithms
- Support the production of scalable and optimised AI/machine learning (ML) models
- Focus on building algorithms for the extraction, transformation and loading of large volumes of realtime, unstructured data to deploy AI/ML solutions from theoretical data science models
- Run experiments to test the performance of deployed models, and identifies and resolves bugs that arise in the process
- Work in a team setting and apply knowledge in statistics, scripting and programming languages required by the firm
- Work with the relevant software platforms in which the models are deployed