Traffic Security Analytics Specialist - TikTok Shop

TikTok Shop is a content e-commerce business with international short video product as the carrier. It is committed to becoming the first choice for users to discover and purchase good products with affordable prices. TikTok Shop business team hopes to provide users with more tailored and efficient consumption experience, enabling merchants to receive reliable platform services in different scenarios such as live e-commerce, short video content e-commerce, thereby making more affordable and high-quality products easily accessible and improving lives.

The E-commerce Security team is responsible for safeguarding the platform's security and creating a safe, trustworthy shopping and business environment for TikTok Shop: allowing consumers to shop with confidence, sellers to operate with peace of mind, and influencers to focus on the enjoyment of bringing goods.

Responsibilities: - Responsible for traffic security analysis and risk operations within TikTok Shop, including crawler detection, malicious traffic identification, abnormal account/device/IP behavior analysis, and fraud traffic governance. - Analyze abnormal traffic patterns based on logs, network, device, and behavioral data to identify suspicious activities and emerging risks. - Participate in the design and optimization of anti-crawling and anti-abuse strategies across key e-commerce scenarios. - Collaborate with engineering, algorithm, and business teams to enhance traffic security and risk control capabilities. - Continuously monitor emerging fraud trends such as AI-driven automation, proxy networks, and black-market abuse activities, and improve prevention strategies accordingly.

Minimum Qualifications: - Bachelor's degree or above in Computer Science, Information Security, Data Analytics, Mathematics, Statistics, or related disciplines. - 2+ years of experience in traffic security analysis, risk control, anti-fraud, anti-crawling, data analytics, or related areas. - Proficient in SQL with strong log analysis and anomaly investigation capabilities; familiar with big data platforms such as Hive, Spark, or ClickHouse. - Familiar with common Web/App traffic risk scenarios, including crawler traffic, bulk registration, fake orders/traffic inflation, automation scripts, proxy/IP pools, emulators, and device farms. - Understanding of HTTP/HTTPS protocols and related concepts such as User-Agent, Referer, Cookie, Header, TLS, and device fingerprinting. - Strong analytical thinking and risk assessment capabilities with high sensitivity to abnormal behaviors.

Preferred Qualifications： - Hands-on experience in anti-crawling, traffic anti-abuse, or traffic security-related algorithms. - Experience in combating black-market or fraudulent activities. - Familiar with AI agent or automated script detection scenarios. - Understanding of cross-border e-commerce business scenarios.