Fraud Risk Data Scientist — E‑Commerce Threat Hunter

TikTok USDS Joint Venture; Seattle (WA); On-site; USD 137,000 - 228,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) match

Parental leave

Disability insurance

Life insurance

Wellbeing benefits

Paid time off

Job summary

TikTok USDS Joint Venture is seeking an Anti-Fraud Data Scientist to mitigate fraud, abuse, and policy violations on TikTok Shop. You will build risk scoring models, dashboards, and automated alerts to protect buyers, merchants, and creators while balancing user experience and growth.

The role requires strong SQL and Python/R skills, a math/statistics background, and 3 years in risk or fraud within tech or e-commerce. This is a US-based, on-site position.

Qualifications

• Bachelor’s degree in mathematics, statistics, computer science, data analytics, or engineering.
• 3 years of relevant experience in anti-fraud, risk management, or data analytics in e-commerce or tech.
• Proficient in SQL and Python/R.

Responsibilities

• Conduct complex exploratory data analysis to uncover emerging fraud vectors and anomalies.
• Define risk metrics, build self-serve dashboards, and real-time alerting systems.
• Develop risk rules and deploy ML models for risk scoring and fraud detection.
• Leverage graph analytics to uncover coordinated fraud rings.
• Design A/B experiments to measure security versus user friction.
• Utilize AI tools to automate risk workflows and analytics.
• Collaborate on data pipelines ensuring cross-border data privacy compliance.

Skills

SQL

Python/R

Anti-fraud

Risk Management

Education

Bachelor’s degree (math/stats/CS)

Job description

TikTok USDS Joint Venture is seeking an Anti-Fraud Data Scientist to mitigate fraud, abuse, and policy violations on TikTok Shop. You will build risk scoring models, dashboards, and automated alerts to protect buyers, merchants, and creators while balancing user experience and growth.

The role requires strong SQL and Python/R skills, a math/statistics background, and 3 years in risk or fraud within tech or e-commerce. This is a US-based, on-site position.