About The Team
The Shopee E-commerce Anti-fraud Algorithm Team is dedicated to enhancing user experience by preventing risks such as low-quality products and fraudulent transactions across search, recommendation, and advertisement scenarios. We are committed to building an industry-leading risk control system that leverages cutting-edge technologies, large-scale deep learning, and emerging AI models.
If you are passionate about e-commerce and risk control, we welcome you to join us in developing advanced anti-fraud algorithms that protect our users and sellers while driving sustainable business growth.
Job Description
As an Anti-Fraud Algorithm Engineer Intern, you will work closely with our risk control and data science teams to support the design and enhancement of anti-fraud systems that protect users and merchants.
Responsibilities
- Algorithm Development: Assist in developing and implementing algorithms to detect fraudulent or abnormal transactions, ensuring platform safety and integrity.
- Model Optimization: Support the exploration and tuning of risk control models to improve accuracy, recall, and scalability.
- Data Analysis: Conduct exploratory data analysis on transaction patterns, user behavior, and merchant activities using anomaly detection and machine learning techniques.
- Risk Monitoring: Help build and refine real-time monitoring tools to identify and respond to potential risks promptly.
- Innovation & Learning: Stay current with the latest advancements in anomaly detection, reinforcement learning, and large-scale AI models, and explore opportunities to apply them in practical scenarios.
What You’ll Gain
- Hands-on experience in real-world anti-fraud systems and risk modeling.
- Exposure to large-scale data platforms and AI-driven solutions.
- Mentorship from experienced algorithm engineers and data scientists.
Requirements
- Currently pursuing a Bachelor’s or Master's Degree or higher in Computer Science, AI, Data Science, or related field.
- Strong programming skills; proficient in Python, C++, or similar languages.
- Solid understanding of data structures, algorithms, and basic machine learning principles.
- Familiarity with at least one deep learning framework (e.g., TensorFlow, PyTorch, MXNet) is a plus.
- Passion for applying algorithms to solve real-world risk control problems in e-commerce.
- Detail-oriented, quick learner, and strong sense of ownership.
- Good teamwork and communication skills.
