TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. U.S. Data Security (“USDS”) is a subsidiary of TikTok in the U.S. This new, security-first division was created to bring heightened focus and governance to our data protection policies and content assurance protocols to keep U.S. users safe. Our focus is on providing oversight and protection of the TikTok platform and U.S. user data, so millions of Americans can continue turning to TikTok to learn something new, earn a living, express themselves creatively, or be entertained. The teams within USDS that deliver on this commitment daily span across Trust & Safety, Security & Privacy, Engineering, User & Product Ops, Corporate Functions and more.

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 alliance team aims to serve merchants and creators in the e-commerce platform to meet merchants' business indicators and improve creators' creative efficiency. By cooperating with merchants and creators, we aim to provide high-quality content and a personalized shopping experience for TikTok users, create efficient shopping tools at seller centers, and promote cooperation between merchants and creators.

We are actively seeking an Applied Scientist to join our Global E-Commerce Alliance Team. This role is centered on developing and implementing innovative machine learning solutions for our recommendation systems in E-Commerce business. The successful candidate will work closely with cross-functional teams, providing expert insight and influencing critical decision-making across multiple areas of our business.

The e-commerce alliance team aims to serve merchants and creators in the e-commerce platform to meet merchants' business indicators and improve creators' creative efficiency. By cooperating with merchants and creators, we aim to provide high-quality content and a personalized shopping experience for TikTok users, create efficient shopping tools at seller centers, and promote cooperation between merchants and creators.

Responsibilities:

- Collaborate with cross-functional teams to design, develop, and deploy sophisticated machine learning algorithms to enhance the performance of our recommendation systems.
- Utilize the ML, NLP, and CV techniques to deal with real-world signals generated from products, creators, merchants, e-commerce transactions, and so on.
- Design and deploy the large recommendation model, in the online learning manner, to serve billions of queries and products.
- Formulate end-to-end machine learning models for recommendation systems, ensuring their efficient and effective operation.
- Analyze extensive, complex datasets to extract meaningful insights, identify opportunities for improvement, and facilitate data-driven decision-making.
- Design and execute experiments, testing and iterating on machine learning models to optimize recommendation functions and boost user satisfaction.
- Stay abreast of the latest advances in machine learning and recommendation systems, integrating this knowledge into your work.
- Clearly communicate complex technical concepts, methodologies, and results to a diverse audience, influencing decisions based on your findings.
- Adhere to stringent data governance and privacy protocols, ensuring all user data is handled responsibly and ethically.

In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.