TikTok Shop - Ecommerce Anti-Fraud Data Analyst

TikTok
London
9 months ago
Applications closed

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Marketing Machine Learning Engineer

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.Why Join UsCreation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible. Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day. To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve. Ecommerce's Governance and Experience(GNE) is a global team responsible for ensuring our marketplace is safe and trustworthy for not only users but also sellers and creators. We value user satisfaction and work on policies, rules, and systems to ensure quality. As the Anti-fraud analyst, you will be responsible for building, improving, and monitoring business processes that detect and prevent fraudulent activities in various scenarios including transactions, KYC, and seller-creator affiliation. Roles & Responsibilities: - Apply investigational and analytic skills to monitor, audit, and analyze potential fraudulent cases and produce root cause analysis report with value-added risk mitigation suggestions.- Collaborate with product managers, data scientists, and the engineering team to evaluate the efficiency of existing tools, processes, and models related to fraud management.- Understand the trends and intelligence of fraudulent activities in each market and build intelligence systems to mitigate fraud.- Define key performance metrics and build detailed reporting models for effective tracking, reporting, and feedback on measures implemented.- Drive process implementation and improvement that streamlines determination of fake orders, incentive abuse, and/or other types of fraud.- Communicate findings and complex results to key stakeholders and manage timeline of mitigation projects.

Minimum Qualifications- Bachelor's degree or above with a background in Computer Science, Business Analytic, Math, Statistics, or related field.- Strong data analysis and correlation skills with ability to work through complex and unfamiliar data sets and able to derive the characteristics of different scenarios.- Experience with SQL and analytical tools (SAS, R, Python) is a must. Preferred Qualifications- Comfortable in a matrix organization and to drive cross-functional and cross-regional collaborations.- Strong attention to detail and ability to notice discrepancies in data.- Experience with AI and machine learning is a plus.- Familiarity with risk and fraud in Ecommerce fields is a strong plus.- Past experience working in SEA or EU market is highly preferred.

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