Data Scientist
Core
Develop and implement machine learning models to detect and prevent fraud in real-time payment transactions.
Role type
Machine learning engineer (fraud detection)
Builds
Real-time fraud scoring and decisioning systems for payments platforms
Domain
Fintech / Payments / Fraud Prevention
Deliverable
production ML models
Required skills
Machine learning (supervised/unsupervised, anomaly detection, graph analytics), Python, SQL, Big data tools (Spark, Hadoop), Cloud platforms (AWS, Azure, GCP), Real-time scoring systems, Model deployment frameworks
Preferred skills
Kafka, Core banking/payment systems experience, SAS Studio/Enterprise Guide (via careerplan.io/jobs/R50929-data-scientist-at-firstrand)
Technologies
Python, SQL, Spark, SAS, TensorFlow, PyTorch, scikit-learn, Kafka, AWS, Azure, GCP, Hadoop
Responsibilities
Develop and implement ML models for fraud detection, Build and optimize real-time fraud scoring systems, Analyze large datasets to uncover fraud patterns, Ensure compliance with regulatory and risk frameworks, Collaborate with technology, operations, and product teams
Seniority
Mid-level, hands-on IC
