Machine Learning Engineer/Applied Data Scientist, E-Commerce Risk - USDS

TikTok; Seattle (WA); Hybrid; USD 120,000 - 150,000; Full time

Job summary

A leading company is seeking a Machine Learning Engineer/Applied Data Scientist to join their E-Commerce Risk Control team. You'll build scalable machine learning solutions to combat risks like account abuse and malicious behaviors, enhancing the security of their platforms. The role requires a strong background in machine learning, programming, and data analysis, with a focus on developing robust models. Join a diverse team dedicated to fostering creativity and innovation while ensuring user safety.

Qualifications

• 3+ years of experience in building and deploying large-scale machine learning models.
• Strong understanding of anomaly detection, predictive modeling, and Bayesian inference.

Responsibilities

• Build machine learning solutions to mitigate risks like account abuse and malicious activities.
• Develop fraud detection, anomaly detection, and risk-scoring models using various techniques.

Skills

Java

C++

Python

Scala

R

Ruby

Matlab

Education

Master's degree in Computer Science

PhD in CS

Job description

Machine Learning Engineer/Applied Data Scientist, E-Commerce Risk - USDS

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Responsibilities

About the team

The E-Commerce Risk Control team works to minimize the damage of inauthentic behaviors on TikTok E-Commerce platforms, covering areas such as account integrity, incentive abuse, malicious behaviors, brushing, click-farm, information leakage, etc.

In this team, you'll have the opportunity to be involved in key security initiatives, building scalable, robust, privacy-safe, and product-friendly systems to address evolving challenges in our product ecosystem.

Responsibilities:

• Build machine learning solutions to mitigate risks like account abuse, malicious activities, brushing, click-farm, and information leakage.
• Enhance modeling infrastructure, labels, features, and algorithms for robustness, automation, and generalization.
• Advance risk machine learning practices focusing on privacy, interpretability, and risk analysis.
• Develop fraud detection, anomaly detection, and risk-scoring models using supervised, unsupervised, and deep learning techniques.
• Apply graph-based models to detect fraud networks.

Our organization follows a hybrid work schedule requiring in-office presence 3 days a week, subject to review and change.

Qualifications

Minimum Qualifications:

• Master's degree in Computer Science, Mathematics, Machine Learning, or related STEM field.
• Experience programming in Java, C++, Python, or related languages.
• 3+ years of experience in building and deploying large-scale machine learning models.
• Proficiency with programming and scripting languages like Scala, Python, R, Ruby, or Matlab.
• Strong understanding of anomaly detection, predictive modeling, and Bayesian inference.
• Experience with real-time ML systems, feature engineering, and risk scoring models.
• Ability to communicate results clearly and work independently.

Preferred Qualifications:

• PhD in CS, Machine Learning, Statistics, or related fields.
• 4+ years industry experience in predictive modeling and analysis.
• Experience collaborating with product, operations, and engineering teams.
• Knowledge of explainable AI techniques like SHAP and LIME.

About USDS

TikTok's US Data Security division focuses on data protection and content assurance to keep U.S. users safe. The team spans Trust & Safety, Security & Privacy, Engineering, and other functions.

Data Security Statement

This role involves working with systems safeguarding sensitive data and will require security screening.

Why Join Us

Join TikTok to inspire creativity and bring joy. Our diverse, innovative teams work to create value, foster impact, and grow together in a fast-paced environment.

Diversity & Inclusion

TikTok values diversity and strives to create an inclusive environment that reflects the communities we serve.

USDS Reasonable Accommodation

USDS provides accommodations during recruitment for candidates with disabilities or other protected reasons. Contact us at https://tinyurl.com/USDS-RA for assistance.