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TikTok Shop - Senior Data Scientist, Operations

TikTok
Greater London
1 month ago
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About the TeamThe Data Science team is a global, full-stack data team that plays an important role in empowering and driving the growth of TikTok Shop. Through impactful data insights and data products, the team focuses on areas such as metrics development, product, operation, algorithm improvement, data infrastructure, and data product development. The team enables informed decision-making and helps optimize the performance and effectiveness of TikTok Shop. As a Senior Data Analyst focusing, you will have the opportunity to collaborate closely with a variety of teams within the commerce business, including product, operation, marketing, and other teams. You will be able to leverage your data analytical expertise and strong business acumen to accelerate the growth of commerce business. Responsibilities

  • Responsible for data analysis of e-commerce operation strategy including Merchant Strategy, Creator Strategy, Business performance and reporting;
  • Design monitoring systems independently to reflect any changes of business in time.
  • Cooperate with Ops team to set strategy, . finding potential creators, measuring LTV of users, figuring out the growth strategy of merchants, etc.;
  • Follow up the data analysis of regional operation teams in several overseas markets, support the operation effect and give follow-up optimization suggestions;
  • Cooperate with PM / Ops team / R&D, promote the implementation of optimization scheme, and bring about the actual improvement and growth of the business.

    Minimum Qualifications: - Bachelor's degree or above, majoring in statistics or data science is preferred;
  • At least 3 years of working experience in data analysis and/or science
  • Proficient in SQL and Tableau and/or other relevant languages.
  • Experience operating in an analytical role involving within an e-commerce or similar environment. - Self-driven, ability to learn new information quickly and adapt into ways of working with global staff in a diverse and cross-functional environment. Preferred Qualifications:
  • Familiarity with common statistical methods and applications (A/B testing, probability, regression)
  • Experience with Python or R.

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