DataVisor · Posted 1d ago
Senior Data Scientist (Fraud Detection)
Job relayed by Stapply Data, its source: you apply there.
- Location
- 🇺🇸 Mountain View, United States
- Contract
- Full-time
- Role
- Data science
- Source
- Stapply Data
Stack
- Spark
- Hadoop
- SQL
- Python
- AWS
- GCP
- Azure
The posting
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