We are seeking a skilled machine learning engineer with a security or risk control background to join our team. As a Risk Control Algorithm Engineer Intern, you will need to apply statistical and machine learning techniques for anomaly detection.
Job Description
- Conduct data exploration and statistical analysis based on a deep understanding of business processes, and develop machine learning models to detect various business threats.
- Develop anti-cheating, anti-fraud, and adversarial technologies using data mining, machine learning, deep learning, and unsupervised learning techniques to address business security issues.
- Collaborate with product and technical teams to deploy models, ensuring continuous maintenance, iterative optimization, and product upgrades.
- Drive algorithmic innovation, becoming an industry leader in blockchain risk control by working on areas such as on-chain graph mining, knowledge graphs, and adversarial game theory.
Requirements
- Master's/Ph.D. candidates in Computer Science, Mathematics, Statistics, Information Science, or a related field.
- Proficient in data mining, statistical learning, and deep learning algorithms, with experience in at least one machine learning platform.
- Skilled in Python, Scala, or similar programming languages, with strong coding skills and experience in at least one complete algorithmic modeling project.
- Highly data-sensitive, self-driven in research, interested in security and risk control, and possesses strong communication and collaboration skills.
Preferred Qualifications
- Published papers in CCF B or higher conferences or journals.
- Top 1% placement in modeling competitions, such as Alibaba Tianchi, Alibaba AI Security Contest, Kaggle, or KDD competitions.
- Experience with open-source contributions, with a demonstrated influence and innovativeness in the field.
