TikTok
Machine Learning Engineer Graduate (E-Commerce Risk, USDS) - 2024 Start (MS)
TikTok, Seattle, Washington, us, 98127
Responsibilities
- Build machine learning solutions to respond to and mitigate business risks in TikTok products/platforms. Such risks include and are not limited to abusive account integrity, scalpers, deal-hunters, malicious activities, brushing, click-farm, information leakage etc.- Improve modeling infrastructures, labels, features and algorithms towards robustness, automation and generalization, reduce modeling and operational load on risk adversaries and new product/risk ramping-ups.- Up-level risk machine learning excellence on privacy/compliance, interoperability, risk perception and analysis.
Qualifications
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- Experience 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#J-18808-Ljbffr
- Build machine learning solutions to respond to and mitigate business risks in TikTok products/platforms. Such risks include and are not limited to abusive account integrity, scalpers, deal-hunters, malicious activities, brushing, click-farm, information leakage etc.- Improve modeling infrastructures, labels, features and algorithms towards robustness, automation and generalization, reduce modeling and operational load on risk adversaries and new product/risk ramping-ups.- Up-level risk machine learning excellence on privacy/compliance, interoperability, risk perception and analysis.
Qualifications
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- Experience 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#J-18808-Ljbffr