AI Fraud Protection Specialist

2 days ago

Sydney, New South Wales, Australia beBeeFraud Full time $180,000 - $220,000
Job Title: Machine Learning Specialist for Fraud Detection

We're seeking a talented Machine Learning Specialist to join our team. As a specialist in this role, you will be responsible for building and deploying AI models using transformer architectures, GNNs, and unsupervised learning for anomaly and abuse detection. You will work closely with engineering, product, compliance, and security teams to build end-to-end machine learning systems detecting, explaining, and preventing fraudulent behaviors in real time.

The ideal candidate should have hands-on experience in machine learning and fraud detection, ideally in fintech, e-commerce, or Web3. Strong background in graph machine learning, GNNs, clustering algorithms, transformer models, attention mechanisms, and fraud detection techniques is required. Proficiency in Python and ML frameworks like PyTorch/TensorFlow is also essential. Familiarity with big data processing tools (Spark, Hive) and real-time data pipelines (Kafka, Flink) is a plus.

Responsibilities:
  • Design, build, and deploy AI models using transformer architectures, GNNs, and unsupervised learning for anomaly and abuse detection.
  • Build scalable graph learning pipelines to detect communities of malicious actors and their on-chain behavioral patterns.
  • Implement high-performance fraud scoring systems operating in real time at massive scale.
  • Collaborate with campaign & marketing teams to identify abuse vectors in rewards, referral, and incentive systems.
  • Conduct regular performance evaluations of ML models and continuously improve them using new research and adversarial learning techniques.
  • Support fraud investigation workflows by providing interpretable model results and actionable insights.

Requirements:
  • Bachelor's or Master's degree in Computer Science, Data Science, or related field.
  • 5+ years of hands-on experience in machine learning and fraud detection, ideally in fintech, e-commerce, or Web3.
  • Strong background in:
    • Graph machine learning, GNNs, and clustering algorithms
    • Transformer models and attention mechanisms
    • Fraud detection techniques, including anomaly detection and behavioral scoring
    • Feature engineering from high-dimensional, noisy, and heterogeneous data sources
    • Proficiency in Python and ML frameworks like PyTorch/TensorFlow.
    • Familiarity with big data processing tools (Spark, Hive) and real-time data pipelines (Kafka, Flink).
    • Solid understanding of EVM-compatible blockchain data (transactions, contract calls, logs) and wallet behaviors.
  • Preferred:
    • Experience with fraud rule engines or security scoring systems.
    • Familiarity with tools like Chainalysis, Tenderly, Alchemy, or similar blockchain analytics platforms.

What We Offer:
  • Competitive salary and benefits
  • Opportunity to work on cutting-edge risk systems securing one of the world's most active trading ecosystems
  • A collaborative, fast-paced environment valuing ownership, speed, and innovation
  • Access to a global team of experts across fraud, security, AI, and blockchain

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