Machine Learning Engineer, Ecommerce Risk Control

The E-Commerce Risk Control (ECRC) team's mission is : - To protect TikTok e-commerce users, including and beyond buyer, seller, creator; - To make Tiktok e-commerce the safest and most trusted place worldwide to transact online by securing the integrity of the e-commerce ecosystem and providing a safe shopping experience on the platform; - Through building software systems, risk models and operational processes, as well as collaborating with many cross-functional teams and stakeholders.

The ECRC team works to prevent and detect any risk attempts in Tiktok e-commerce platforms (e.g. TikTok Shop, Fanno) and to mitigate the negative impact on our customers and Selling Partners (Sps), covering multiple classical and novel business risk areas such as account integrity, incentive abuse, malicious activities, brushing, click-farm, information leakage etc. We achieve our mission by a) developing state-of-art Machine Learning (ML) solutions to prevent customers, SPs, and Tiktok from being impacted by bad actors’ actions and practices to gain unfair business advantages; b) empowering Tiktok teams, both internal to GNE and external, to reduce risk attempts by utilizing our mechanisms.

Responsibilities: - Invent, implement, and deploy state of the art machine learning algorithms, to respond to and mitigate business risks in Tiktok products/platforms. - Build prototypes and explore conceptually new solutions, define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams - Collaborate with cross-functional teams from multidisciplinary science, engineering and business backgrounds to enhance current automation processes - Develop efficient data querying infrastructure for both offline and online analysis, 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. - Maintain technical documents and communicate results to diverse audiences with effective writing, visualizations, and presentations

Minimum Qualifications - Master degrees in Computer science, Mathematics, Machine Learning, or other relevant STEM majors (e.g. finance if applying for financial fraud roles). Experience programming in Java, C++, Python or related language - 3+ years of hands on experience in building and delivering machine learning models for large-scale projects. - Track record of developing and implementing models and visualizations using programming and scripting (Scala, Python, R, Ruby, and/or Matlab). - Experience using various forecasting, machine learning and statistical tools and communicating results, plans and/or risks clearly. - Ability to think creatively and solve problems.

Preferred Qualifications: - A PhD in CS, Machine Learning, Statistics, Operations Research, or relevant field - 4+ years of industry experience in predictive modeling and analysis - Experience collaborating with product, operations and engineering teams is a plus. - Excellent analytical and communication skills and ability to influence stakeholders. - Experience in e-commerce / online companies in fraud / risk control functions.