Data Scientist

• Take ownership of data preparation tasks, from querying raw sources to cleaning, transforming, and structuring datasets for robust analysis and model evaluation.
• Design and implement data quality frameworks to ensure integrity, identify anomalies, and handle missing or imbalanced data effectively.
• Analyze AI and LLM-driven outputs using metrics like accuracy, precision, recall, and F1, and perform deep dives into performance trends and errors.
• Translate evaluation results into compelling narratives about model ROI, efficiency gains, and clinical outcomes.
• Build clear and visually engaging dashboards using tools such as Plotly, Matplotlib, or similar frameworks—selecting visualization methods that best communicate results to technical and non-technical stakeholders.
• Collaborate closely with clinical leaders, NLP engineers, and researchers to structure pipelines and QA model outputs for benchmarking and continuous improvement.
• Partner with the research and product teams to support data-driven decision-making in product development, evaluation, and client success.
• Contribute to internal reports, manuscripts, and white papers that turn technical findings into actionable insights.

Applied Data Scientist – Insights & Outcomes

Junior Data Scientist

Data Scientist I, Real World Data Science

Data Scientist II

Data Scientist

Junior Data Scientist