Algorithm Engineer Intern, Anti-fraud

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 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.