Computer Vision Data Scientist
Remote · Poland
Job Summary
Computer Vision Data Scientist responsible for analyzing large-scale receipt data for fraud patterns, developing statistical methods to detect inconsistencies, designing feature engineering strategies that combine OCR, visual embeddings, and behavioral signals, and building fraud-detection ML models. Will implement threshold optimization for varying risk levels, develop scalable fraud scoring systems, and create interpretable scoring frameworks for manual review teams. 100% remote work with a focus on fraud detection in retail/e-commerce contexts, leveraging a tech stack including GenAI and ML tools.
Required Qualifications
- 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
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