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. They collaborate with cross-functional stakeholders to improve TikTok infrastructures, services, tools, and algorithms, striving for a higher standard of privacy and security. The BRIC team focuses on measuring and minimizing damage from inauthentic behaviors across TikTok and its extended platforms, 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 graduates to join our team in 2026. This role offers opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth within TikTok. Successful candidates must commit to an onboarding date by the end of 2026.
Responsibilities
- Analyze business and security data to uncover evolving attack motions, identify weaknesses and opportunities in risk defense solutions, and explore new areas based on 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 establish 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 abusive accounts, fake engagements, spammy redirection, scraping, and fraud.
- Take ownership of the technical measurement and evaluation of risk levels for 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, leveraging data to facilitate collaboration.
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, or measurement-and-experiment-driven product iteration.
- Strong ownership, proactive and skillful communication, and the ability to handle high complexity, urgency, and cross-functional alignment.
Preferred Qualifications
- Industry experience in relevant data science domains such as search and ranking, recommendation, ads/monetization, anti-fraud/abuse, or financial risks.
- Adept at telling data stories.