Senior Data Scientist (Fraud Detection)

Join our Fraud Detection team as a Senior Data Scientist. In this dual-track role, you will develop machine learning systems to catch fraud at scale and lead investigations into specific fraud cases. You will work with large-scale data, develop predictive features, and produce technical reports for various stakeholders. This is an opportunity to grow your skills in a fast-paced, data-driven environment while making a real impact in the fight against fraud.

• Lead the full lifecycle of fraud detection features and models, from ideation and data exploration to prototyping, productionizing, and monitoring.
• Develop highly predictive features from complex, large-scale, multi-dimensional data, including user behavior, device intelligence, network graphs, and transaction records.
• Lead investigations into complex fraud cases across identities, accounts, devices, and transaction surfaces. Reconstruct attacker sequences and hypothesize actor intent and tooling.

• 3+ years of applied experience in fraud detection, cybersecurity, or a related adversarial/high-velocity risk domain (fintech, consumer payments, banking, SaaS, marketplace risk, or security research)
• Master's or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field
• Hands-on experience with the machine learning lifecycle in a production environment
• Solid understanding of both classic machine learning models (Logistic Regression, Gradient Boosting, etc.)
• Investigator mindset: demonstrated skill in pattern synthesis, hypothesis testing, and triaging signal from noise in ambiguous, adversarial cases — not just building and monitoring models
• Excellent communication skills — able to explain complex, ambiguous, or technical behavior clearly to both technical and non-technical audiences, including customers and executives
• Strong programming skills in Python (must-have) and proficiency with SQL; experience with PySpark is a significant plus
• Experience with large-scale data tools (Spark, Hadoop, etc.) and cloud platforms (AWS, GCP, Azure)
• Professional proficiency in written and spoken English, with the ability to collaborate effectively in a global, cross-functional team