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