About the Role
The Business Risk Integrated Control (BRIC) team at TikTok is dedicated to protecting TikTok users (including content consumers, creators, and advertisers), securing platform health, and ensuring the authenticity of community experience. The team collaborates with cross-functional stakeholders to enhance TikTok's infrastructures, services, tools, and algorithms, aiming for higher standards of privacy and security.
The BRIC team actively works to measure and minimize damage from inauthentic behaviors across TikTok and its extended platforms. This includes addressing classical and novel integrity/security areas such as fake accounts, fake traffic, spam, scraping, cyberbullying, live room risks, incentive fraud, and monetization abuse.
We are seeking talented individuals to join our team in 2026. As a graduate, you will have opportunities to pursue bold ideas, tackle complex challenges, and experience limitless growth, launching your career in an environment of infinite inspiration at TikTok. Successful candidates must be able to commit to an onboarding date by the end of 2026.
Responsibilities
- Analyze business and security data, uncover evolving attack motions, identify weaknesses and opportunities in risk defense solutions, and explore new areas based on these discoveries.
- Define risk control measurements, quantify, generalize, and monitor risk-related business and operational metrics. Align risk teams and stakeholders on numeric risk control goals, promoting impact-oriented, data-driven data science practices for risks. Detect abnormal changes in metrics and build processes for root cause analysis.
- Design and build A/B experiments to meet various business needs. Develop rules and models to respond to and mitigate business risks for different TikTok products, including but not limited to abusive accounts, fake engagements, spammy redirection, scraping, and fraud.
- Take ownership of the technical measurement and evaluation of risk levels in specific business areas (e.g., short video platform, user growth, live streaming). Define and coordinate the planning, execution, and generalization of risk solutions.
- Drive and take responsibility for implementing data science best practices in risk analytics and modeling across all stakeholders. Leverage data to facilitate collaboration among these stakeholders.
Minimum Qualifications
- Final year or recent graduate with a background in computer science, statistics, or other relevant, machine-learning-heavy majors.
- Proficiency in data science analytical tools, such as SQL, R, and Python.
- Possess at least one advantage among risk control, statistical problem solving, and measurement-and-experiment-driven product iteration.
- Strong ownership, proactive and skillful communication, and the ability to manage high complexity, urgency, and cross-functional alignment.
Preferred Qualifications
- Industry experience in relevant data science domains. Example topics include (but are not limited to): search and ranking, recommendation, ads/monetization, anti-fraud/abuse, and financial risks.
- Good at telling data stories.