Computer Vision Data Scientist

This role involves analyzing large-scale receipt data to identify fraud patterns and anomalies, developing statistical methods and machine learning models for fraud detection, and designing comprehensive fraud scoring systems. The position requires expertise in hypothesis testing, time series analysis, and anomaly detection, with a focus on optimizing precision and recall for different risk levels. The ideal candidate will have experience in computer vision, image processing, and high-volume transaction processing, along with a strong understanding of retail and e-commerce fraud patterns.