Data Scientist
Tasks
- Analyze false positives and false negatives impact
- Analyze model performance by clinical and payer segment
- Build ground truth datasets
- Define compute and document production readiness metrics
- Design evaluation samples and sampling plans
- Develop predictive and machine learning models
- Document model design assumptions and limitations
- Ensure PHI handling for HIPAA compliance
- Maintain and recalibrate production models
- Maintain evaluation tooling and traceable experiments
- Monitor deployed model accuracy calibration and drift
- Produce audit readiness evidence of validation and evaluation
- Provide specifications evaluation criteria and acceptance thresholds for production
- Reproduce and verify external partner results
- Support model governance with decision traceability
- Translate clinical problems into analytical problems
- Validate model behavior with clinical judgment
Perks/Benefits
Skills/Tech-stack
Agent-based | Agent-based systems | Concept drift | Data Annotation | Data Pipelines | Data Quality | Databricks | Ground Truth | Human-in-the-loop | Language Models | Language Processing | Large Language Models | Machine Learning | Microsoft Azure | Model Evaluation | Model Monitoring | Model calibration | Natural Language | Natural Language Processing | Performance Metrics | Predictive Modeling | Prompt engineering | Python | Reproducibility | SQL | Sampling design | The Loop | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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