Machine Learning Engineer/Applied Data Scientist, E-Commerce Risk Control - USDS
Seattle, Washington, United States
About the team
The E-Commerce Risk Control team works to minimize the damage of inauthentic behaviors on Tiktok E-Commerce platforms, covering multiple classical and novel business risk areas such as account integrity, incentive abuse, malicious behaviors, 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 evolution of a phenomenal product eco-system. The work needs to be fast, transferable, while still down to the ground to make quick and solid differences.
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, scalper, deal-hunter, 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 in privacy/compliance, interpretability, risk perception and analysis.
- Build fraud detection, anomaly detection, and risk-scoring models using supervised, unsupervised, and deep learning techniques.
- Apply graph-based models for detecting fraud networks
In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.
The E-Commerce Risk Control team works to minimize the damage of inauthentic behaviors on Tiktok E-Commerce platforms, covering multiple classical and novel business risk areas such as account integrity, incentive abuse, malicious behaviors, 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 evolution of a phenomenal product eco-system. The work needs to be fast, transferable, while still down to the ground to make quick and solid differences.
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, scalper, deal-hunter, 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 in privacy/compliance, interpretability, risk perception and analysis.
- Build fraud detection, anomaly detection, and risk-scoring models using supervised, unsupervised, and deep learning techniques.
- Apply graph-based models for detecting fraud networks
In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Job stats:
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Categories:
Data Science Jobs
Engineering Jobs
Machine Learning Jobs
Tags: Deep Learning E-commerce Machine Learning Privacy Security
Perks/benefits: Team events
Region:
North America
Country:
United States
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