Data Scientist – Fraud Detection Project

We are inviting a passionate Data Scientist to join our project — an AI-native fraud prevention company building systems that stop financial scams before money moves. We’re looking for a passionate AI / Data Scientist to join our mission of detecting and disrupting scam activity across social media, web platforms, and on-chain transactions. You’ll work alongside talented AI engineers, developers, and security experts to build advanced models that directly reduce global fraud and scam losses. This is an opportunity to apply your skills to a high-impact problem with significant real-world stakes.

What You’ll Do:

• Design, train, and evaluate machine learning models to detect malicious behavior across textual and numeric data
• Build fraud detection systems that blend rule-based logic with supervised and unsupervised ML methods
• Collaborate with product and engineering teams to improve data pipelines, labeling accuracy, and model performance
• Conduct deep error analysis to identify gaps in data, model drift, or labeling errors
• Continuously iterate on models and heuristics using live feedback from scammer interactions, honeypot systems, and financial tracebacks

Technical Stack:

• NLP / LLMs: Building text classifiers, fine-tuning transformers, integrating LLMs into chatbots/agents
• Classical ML: Techniques for analyzing tabular data with temporal components
• Graph-Based Analysis: Detection of scammer clusters and complex, multi-step scams
• Rule-Based Systems: Development and optimization of scoring systems using machine learning methods
• MLOps: Monitoring live model performance, data drift detection, and retraining pipelines in collaboration with the infrastructure team

 Main requirements:

• Excellent analytical and problem-solving skills
• 1+ years of hands-on experience in a Data Scientist position, preferably in fraud, cybersecurity, or other adversarial domains
• Strong experience with data exploration, feature engineering, and training models on realworld, noisy, and often incomplete datasets
• Proficiency in classical ML (e.g., decision trees, ensemble models, anomaly detection) and understanding when these methods outperform neural networks
• Strong experience with NLP, including building models from scratch, fine-tuning existing models, and integrating LLMs for agents/chatbots
• Proficient with ML frameworks such as pandas, scikit-learn, PyTorch, or TensorFlow
• Upper-intermediate or higher proficiency in English

Nice to Have:

• Degree in Computer Science, Mathematics, or related technical fields
• Track record of successful LLM agents/bots integration in production environments
• Experience with Graph Neural Networks, link prediction, or community detection
• Exposure to on-chain data or Web3 systems (wallets, transactions, smart contracts)
• Background in adversarial ML or anomaly detection

The benefits you will get:

• Work on a high-impact mission: stop fraud before it hits victims
• Be part of an elite AI team working on frontier tech with real-world stakes
• Flexible schedule and remote