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Senior Data Scientist, Risk Data Mining - USDS

TikTok

Responsibilities Build rules, algorithms and machine learning models to respond to and mitigate business risks in TikTok products/platforms, such as abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc. Analyze business and security data, uncover evolving attack motion, identify weaknesses and opportunities in risk defense solutions, and explore new space from discoveries. Define risk control measurements. Quantify, generalize and monitor risk-related business and operational metrics. Align risk teams and stakeholders on risk control goals, promoting impact-oriented, data-driven practices. Qualifications Bachelor or higher degrees in computer science, statistics, math, internet security or other relevant STEM majors (e.g., finance for financial fraud roles). Solid data science skills. Proficiency in SQL, R and Python. Familiarity with machine learning or social/content online platform analytics. Bonus for proficiency in modern machine learning applications. Ability to think critically and communicate in a result-oriented, data-driven manner with high autonomy. About USDS TikTok is the leading destination for short-form mobile video. U.S. Data Security ("USDS") is a subsidiary of TikTok in the U.S. This security-focused division focuses on data protection policies and content assurance protocols to keep U.S. users safe. Our teams span Trust & Safety, Security & Privacy, Engineering, User & Product Ops, and more. Data Security Statement: This role requires the ability to work with and support systems designed to protect sensitive data. The role is subject to strict national security-related screening. Reasonable Accommodation USDS is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs, or other protected reasons. If you need assistance or a reasonable accommodation, please reach out to us at #J-18808-Ljbffr TikTok

Vacancy posted 12 hours ago
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