计算机视觉数据科学家

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