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Job Description
📋 Description
- Build, evaluate, and deploy ML models for risk scoring and vendor risk.
- Analyze large datasets to identify patterns and anomalies.
- Ensure model accuracy, robustness, and scalability in production.
- Collaborate with product and engineering teams to define DS requirements.
- Contribute to code reviews and DS best practices.
- Stay updated on new research and share findings with stakeholders.
🎯 Requirements
- Advanced degree in a quantitative field or equivalent experience.
- 5+ years of DS/ML experience.
- Proficient in Python and frameworks (scikit-learn, XGBoost, MLFlow, PyTorch).
- Experience with cloud data pipelines (AWS, GCP, or similar).
- Strong ML fundamentals, evaluation, and deployment knowledge.
- Effective communicator and collaborative team player.
🎁 Benefits
- Competitive salary and stock options.
- Health benefits and unlimited PTO.
- Parental leave and tuition reimbursements.
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