Data Scientist, Trust & Safety - USDS

About TikTok U.S. Data Security
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 subsidary 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.

Team Intro
We are seeking an experienced Data Scientist to join the Risk and Response - Detection and Automation Team within US Trust & Safety (T&S). TikTok T&S helps ensure that our global community is safe and empowered to create and enjoy content across all of our applications.
As a Data Scientist on the Risk and Response - Detection and Automation Team, you will contribute to the discovery, investigation, and remediation of high harm issues and behavior on platform within our Detection Engineering Program. Detection Engineering focuses on the creation and maintenance of proactive logic to identify high harm content at scale to prevent harm to users and to the company. This role will work internally with the Automation Engineering pillar within the larger Detection and Automation team, and cross functionally with other Trust and Safety teams and Security teams. Examples of use-cases you will help to develop include finding high harm leakage in areas of youth safety, exploitation and abuse, and violent behaviors, just to name a few. Detections can take the form of SQL jobs, lightweight topic classification models, and even large language model solutions.

Our Automation and Detection team performs a critical function that supports our efforts to address objectionable or disturbing content. Content that this Data Scientist interacts with includes images, video, and text related to every-day life, but it can also include (but is not limited to) bullying; hate speech; child abuse; sexual assault; torture; bestiality; self-harm; suicide; and murder.

It is possible that this role will be exposed to harmful content on a daily basis.

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.

Responsibilities
- Improve consistency and efficiency throughout US Trust & Safety's Detection Engineering program by architecting and shipping high precision use-cases via SQL and different modeling strategies in Python.
- Work directly with stakeholders to inform, refine, and validate concepts. We ideate a majority of the work we develop, which means capturing need and maturing it from MVP to production.
- Work with cross functional teams globally to ensure alignment, collect feedback on detections, and deploy solutions to get cross functional adoption.
- Raise the effectiveness of tooling and detection solutions through metrics collection and insights.
- Provide mentorship and guidance for data analysts on the team.