The opportunity
Analyze large-scale on-chain data to identify anomalous transactions and develop robust detection mechanisms.
What you'll do
Analyze large-scale on-chain data to identify anomalous transactions and develop robust detection mechanisms.
Enhance transaction detection capabilities across networks and refine risk monitoring frameworks.
Use community discovery algorithms to identify associated malicious accounts: and provide actionable intelligence.
Design a comprehensive data prevention and control system integrating on-chain and off-chain data sources.
Utilize supervised and unsupervised machine learning techniques to identify: anomalous patterns (e.g. irregular transaction volumes, unusual wallet behaviors, atypical token movements) across decentralized networks.
What they're looking for
- Over 5 years of experience in blockchain, anti-fraud, risk control, or: related fields, strong analytical skills and attention to detail.
- Proficient in SQL and experienced in using Python and Spark/Flink; solid: understanding of common data mining and machine learning algorithms;
- Strong problem-solving and goal-oriented mindset with a proactive learning: attitude; keen interest in Web3 security;
- Ability to work collaboratively in a fast-paced, dynamic environment.
- English proficiency sufficient for professional communication;
- Knowledge of blockchain and familiarity with on-chain data are considered strong pluses.
