Computer Vision Data Scientist

Computer Vision Data Scientist In your new role, you will: Analyze large-scale receipt data for fraud patterns and anomalies Develop statistical methods to detect subtle inconsistencies in receipt data Design feature engineering strategies combining OCR, visual embeddings, and behavioral signals Build and optimize ML models for fraud detection using collected data points Develop fraud scoring algorithms that combine multiple detection signals and model outputs Implement threshold optimization strategies balancing precision and recall for different risk levels Design comprehensive fraud scoring systems Develop weighted scoring mechanisms adaptive to fraud types and retailer patterns Create interpretable scoring frameworks for manual review teams We're Looking For: 4+ years as a data scientist with experience in fraud detection Strong expertise in hypothesis testing, time series, and anomaly detection Hands-on experience with classification, ensemble methods, and deep learning (scikit-learn, XGBoost, PyTorch/TensorFlow) Computer Vision - Strong experience with image processing and embedding, specifically EfficientNet and FAISS, is a plus Experience with high-volume transaction processing and real-time decision systems Knowledge of retail/e-commerce fraud patterns preferred Familiarity with document fraud techniques and anti-fraud methodologies Why join us? Cutting-edge tech stack including GenAI and ML A global team with diverse perspectives 100% remote work Opportunity to influence product direction and company growth Originally posted on Himalayas