Responsibilities
- Refine payment-risk feature engineering and fraud evaluation systems.
- Develop fraud and account-takeover detection models for global payment scenarios.
- Explore sequence models, graph networks, and LLMs for risk-control applications.
- Develop machine learning models to identify cross-border and regional payment risks.
- Optimize modeling workflows to improve development and deployment efficiency and reduce maintenance costs.
- Research and apply advanced machine learning algorithms in the risk-control domain.
Requirements
- Bachelor’s degree or higher in computer science, computer engineering, statistics, applied mathematics, data science, or a related discipline.
- Strong experience with data structures and algorithms.
- Familiarity with at least one of TensorFlow, PyTorch, or MXNet, including training and deployment details.
- Strong coding skills in at least one of Python, Java, C, or C++.
- At least three years of relevant experience preferred.
- Experience in NLP, graph mining, fraud detection, credit risk, payment risk, or search and recommendation systems preferred.
- CCF A/B papers or competition awards preferred.
Categories
About ByteDance
ByteDance is a global incubator of platforms at the cutting edge of commerce, content, entertainment and enterprise services - over 2.5bn people interact with ByteDance products including TikTok. Creation is the core of ByteDance's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. At ByteDance, we create together and grow together. That's how we drive impact - for ourselves, our company, and the users we serve. We are committed to building a safe, healthy and positive online environment for all our users. We have over 110,000 employees based in more than 30 countries globally. Join us.