Summer Intern- Risk Control Algorithm

Overview

You'll help build and iterate risk control and anti-fraud systems, using data analysis, feature engineering, and machine learning to protect platform integrity across business lines.

This is a full-time summer 2026 internship (5+ months). Strong performers will be considered for a return offer.

Responsibilities

● Support the development and iteration of risk control and anti-fraud frameworks across multiple business scenarios

● Analyze fraud patterns (scraping, fake transactions, account abuse, bonus farming, etc.); contribute to strategy deployment to improve intercept rates and reduce false positives

● Help build real-time risk monitoring modules; assist with incident response for emerging fraud vectors

● Participate in feature engineering and model development/optimization (XGBoost, Decision Trees, Random Forests)

● Collaborate cross-functionally to deploy risk tools and maintain internal knowledge documentation

Qualifications

● Bachelor's degree or above in CS, Statistics, Mathematics, Data Science, or a related field

● Proficient in SQL for data querying and cleaning; solid Python skills (Pandas, NumPy, Scikit-learn)

● Basic familiarity with risk control and anti-fraud concepts

● Strong logical thinking, quick learner, and collaborative team player

Bonus Points

● Hands-on experience with risk algorithms (Decision Trees, Random Forests, XGBoost, etc.)

● Experience with feature engineering or basic model development

● Prior internship or project experience in risk control or anti-fraud