Data Scientist, E-Commerce Anti-Fraud

About the Team

E-commerce's Governance and Experience is a global team responsible for ensuring our TikTok Shop marketplace is safe and trustworthy for users, sellers, and creators. We value user satisfaction and work on policies, rules, and systems to ensure quality. The USDS Risk Control and Security team within GNE focuses on fighting various forms of fraud and abuse within the TikTok Shop ecosystem via insight generation, scaled enforcement, automation, and prevention.

About the Role

The Risk Control & Security Anti-Fraud Data Scientist role focuses on mitigating fraud, abuse, policy violations and business risks for TikTok's e-commerce platform, TikTok Shop. This role is critical in protecting our buyer, merchant, and creator communities, ensuring compliance with internal policies and industry regulations while balancing customer experience and business growth.

Responsibilities

• Conduct complex, exploratory data analysis to uncover emerging fraud vectors, behavioral anomalies, and latent platform vulnerabilities.
• Define risk metrics, construct self-serve dashboards, and build real-time automated alerting/circuit breakers for rapid threat response and executive visibility.
• Formulate, validate, configure, and deploy risk strategies and rules to mitigate fraud with minimal false positives. Drive the end-to-end development, deployment, and continuous monitoring of real-time machine learning models for risk scoring and fraud detection.
• Leverage graph analytics, clustering, and entity-resolution techniques to uncover coordinated fraud rings and collusive attacks.
• Design and evaluate rigorous A/B experiments to measure the trade-offs between security, financial loss, and legitimate user friction.
• Leverage modern AI tools and LLMs to automate risk workflows, optimize analytics, and streamline detection capabilities.
• Partner on robust data pipeline infrastructure (including USDS operations) to ensure strict adherence to cross-border data privacy and compliance standards.

Minimum Qualifications

• Bachelor's degree in mathematics, statistics, computer science, data analytics, or engineering
• Proficient in SQL and Python/R
• 3+ years of relevant experience in one of the following areas: Anti-fraud, Risk Management, Trust & Safety, Data Analytics, or Data Science in e-commerce or the general tech industry

Preferred Qualifications

• Familiarity with AI-enabled workflows and hands-on experience building or implementing AI-powered tools, automations, or solutions.
• Excellent communication skills with the ability to work independently with global teams
• Proactive, data-driven, results-oriented, and a high desire to learn and contribute
• Ability to navigate ambiguity and show good judgement

Pay

The base salary range for this position in the selected city is $136,800 - $228,000 annually. Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits

• Day one access to medical, dental, and vision insurance
• 401(k) savings plan with company match
• Paid parental leave
• Short-term and long-term disability coverage
• Life insurance
• Wellbeing benefits
• 10 paid holidays per year
• 10 paid sick days per year
• 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure)

Schedule

On-site presence across teams allows the company to operate with greater speed, alignment, and agility — especially in areas like real-time decision-making, team development, and integrated execution. As such, the company is shifting from a hybrid work model to a fully in-person schedule up to 5 days a week.