Data Scientist - Analytics, Trust & Safety

Tik Tok

Full time

Mountain View, CA, USA

Sep 20


TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy.

TikTok has global offices in Los Angeles, Dublin, New York, London, Paris, Berlin, Dubai, Mumbai, Singapore, Jakarta, Seoul, and Tokyo. The Trust & Safety policy team at TikTok help ensure that our global community is safe and empowered to create and enjoy content across all of our applications while protecting our brand.

As a Data Scientist on our Trust & Safety team you are instrumental in ensuring we use data analysis to keep our users and community safe. You will help scope out projects, ideate on new strategies, and most importantly, use data to find insights, diagnose problems and tell compelling stories. You will work closely with product manager, engineers, operations teams, and policy specialists on measuring risks, and detecting and preventing negative experiences on our product.


- Use data to identify trends, conduct root cause analysis and suggest potential opportunities for process improvements.

- Develop metrics to evaluate risks of the platform and the effectiveness of safety programs.

- Conceptualize, develop and maintain dashboards for risk detection and monitoring.

- Devise data-driven strategies to proactively identify, detect, and mitigate risk to our users and community.

- Influence stakeholders through data-based recommendations and mobilize cross-functional teams by telling compelling stories with data.


- 2+ years of experience in data science or quantitative analysis.

- Experience with SQL, ETL, R/Python.

- Degree in a quantitative discipline (e.g., Statistics, Economics, Computer Science, Mathematics) or equivalent practical experience.

- Strong communication skills across technical and non-technical audiences and the ability to synthesize and communicate complex concepts and analyses in easy to understand ways.

- Experience with data modeling and statistical analysis techniques, including: hypothesis testing, model evaluation, and common regression and classification algorithms.


- Experience of working in Trust and Safety at a tech company.

- Experience in deep learning, distributed computing (Hive/Hadoop), or social network analysis.

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