Data Scientist

• Design and implement comprehensive evaluation strategies for AI models, including both offline and online (production) settings
• Conduct statistical analyses and hypothesis testing to assess model accuracy, precision, recall, F1 score, ROC-AUC, and other relevant performance metrics
• Collaborate with clinical data labeling teams, ML engineers and data scientists to define validation datasets, ground truth standards, and performance benchmarks
• Analyze model outputs to identify strengths, weaknesses, and potential biases, and provide actionable recommendations for improvement
• Develop and maintain metrics, dashboards, and reports to monitor model performance, drift, and stability over time
• Communicate findings and recommendations to technical and non-technical stakeholders through clear visualizations and presentations
• Develop and maintain documentation and metrics for data quality, profiling results, and value assessments to support transparency and continuous improvement.

Senior Data Scientist, AI RWD

Engineering & Data Science Specialist – Applied AI Evaluations