Machine Learning Engineer - E-Commerce Risk Contro...

Job description


TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Singapore, Jakarta, Seoul and Tokyo.

The E-Commerce Risk Control (ECRC) Team Is Missioned

  • To protect Tiktok E-Commerce users, including and beyond buyer, seller, creator;
  • By securing the integrity of our ecommerce ecosystem and providing a safe shopping experience on the platform;
  • Through building infrastructures, platforms and technologies, as well as collaborating with many cross-functional teams and stakeholders.

The ECRC team works to minimize the damage of inauthentic behaviors on Tiktok E-Commerce platforms (e.g. TikTok Shop, Jumanji, Fanno), covering multiple classical and novel community and business risk areas such as account integrity, incentive abuse, malicious activities, brushing, click-farm, information leakage etc.

In this team you'll have a unique opportunity to have first-hand exposure to the strategy of the company in key security initiatives, especially in building scalable and robust, intelligent and privacy-safe, secure and product-friendly systems and solutions. Our challenges are not some regular day-to-day technical puzzles -- You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolvement of a phenomenal product eco-system. The work needs to be fast, transferrable, while still down to the ground to making quick and solid differences.


  • Build rules, algorithms and machine learning models, to respond to and mitigate business risks in Tiktok products/platforms. Such risks include and are not limited to account integrity, scapler,deal-hunter, malicious activities, brushing, click-farm, information leakage etc.
  • Analyze business and security data, uncover evolving attack motion, identify weaknesses and opportunities in risk defense solutions, explore new space from the discoveries.
  • Define risk control measurements. Quantify, generalize and monitor risk related business and operational metrics. Align risk teams and their stakeholders on risk control numeric goals, promote impact-oriented, data-driven data science practices for risks.


  • Bachelor or degrees above in computer science, statistics, math, internet security or other relevant STEM majors (e.g. finance if applying for financial fraud roles).
  • At least 5 years with solid data science skills. Proficiency in statistical analytical tools, such as SQL, R and Python.
  • Familiarity with machine learning or social/content online platform analytics. Bonus given to proficiency in modern machine learning applications.
  • Ability to think critically, objectively, rationally. Reason and communicate in result-oriented, data-driven manner. High autonomy.

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