Computer Vision Data Scientist
Tasks
- Analyze receipt data for fraud patterns
- Build and optimize fraud detection models
- Create interpretable models for manual review
- Detect anomalies and inconsistencies
- Develop fraud scoring algorithms
- Engineer features using OCR and visual embeddings
- Implement adaptive weighted fraud scoring
- Optimize classification thresholds for risk levels
Perks/Benefits
Skills/Tech-stack
Anomaly Detection | Classification | Computer Vision | Decision Systems | EfficientNet | Ensemble Methods | Faiss | Feature Engineering | Hypothesis Testing | Image Processing | Image embeddings | Machine Learning | Optical character recognition | PyTorch | Python | Real Time | Real-time decision systems | Scikit-learn | TensorFlow | Time Series | XGBoost
Education
N/A
Roles
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