About the Team As a Data Scientist in TikTok's Trust and Safety team, you will drive data driven decisions and forming roadmaps in ensuring that TikTok remains a safe, trustworthy, and risk-free environment. By implementing your domain knowledge, you will help diagnose, triage, and treat large-scale safety issues. You will scope out projects, use ground-truth data to inform strategies and influence product design. You will partner with a variety of stakeholders across the product, operations, policy, and engineering teams - both locally and globally. You will work with the stakeholders to implement strategies and design product to proactively detect and disarm safety incidents, while protecting creator experience. Responsibilities: - Design and implement comprehensive metrics and quantitative measurement frameworks to evaluate the effectiveness of risk control policies. Continuously refine measurement methodologies to track risk control capabilities accurately; - Lead strategic planning by analyzing industry trends, competitive landscapes, and internal data. Translate insights into actionable business plans to improve platform safety and policy operability; - Partner with stakeholders to achieve targets using data-driven approaches, such as monitoring policy impacts on risk control capabilities, leveraging statistical methods to establish an efficient decision-making system, standardizing reusable analytical methodologies and tools to enhance team efficiency; - Collaborate with XFN teams to align priorities, communicate data-backed recommendations, and drive implementation. Foster organization-wide adoption of data-inspired practices.
Minimum qualifications: - Bachelor's degree or above in mathematics or statistics-related majors, with a solid foundation in statistical, hypothesis testing theories and experimental design; - Solid experience in quantifying complex problems with many impacting factors, and use statistical methods to seek answers, such as designing experiments, making causal inference. Proficient in data analysis and statistical analysis tools such as SQL, Python, R, Excel and Tableau; - 2+ years of experience in data science related industry, with rich experience in designing success metrics and A/B testing and a deep understanding of risks in globalized products. Preferred experience: - Ability to/knowledge of network detection and good at cooperating with the Engineer and Product teams to design the scalable workflow. - Ability to translate technical findings into clear, strategic recommendations for non-technical stakeholders; - Proven track record of working cross-functionally to drive data-informed initiatives in fast-paced environments; - Acute ability to grasp company product-related industry technology development trends, and possess strong macro analysis and decision-making capabilities.
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