ROI & Performance Metrics: Expertise in defining, tracking, and evaluating ROI metrics for AI/ML projects, particularly within the healthcare domain. Ability to develop standardized frameworks, baselines, and processes to measure project impact, including cost savings, operational effectiveness, and patient outcomes.

AI/ML Performance Evaluation: Proficiency in creating and maintaining dashboards to monitor model performance (accuracy, precision, recall, etc.) and analyzing trends, anomalies, and areas for improvement. Experience in collaborating with teams to drive model retraining and enhancements.

Data Analysis & Technical Expertise: Strong programming skills in Python and SQL for data manipulation, statistical analysis, and building scalable code. Expertise in developing and maintaining Tableau or Looker Studio dashboards, and applying statistical methods to assess AI/ML project impact on patient care and operational efficiency.

Healthcare Domain Knowledge: Familiarity with EHR systems, healthcare data structures, and key healthcare metrics (e.g., readmission rates, hospital-acquired conditions). Understanding of HIPAA compliance and healthcare-specific standards.

Collaboration & Communication: Ability to engage and collaborate effectively with cross-functional teams, including clinicians, IT professionals, and executive leadership. Strong communication skills to translate complex technical findings to both technical and non-technical stakeholders.

Continuous Improvement & Innovation: Demonstrated track record of staying current with AI/ML and healthcare analytics trends, actively recommending enhancements, and contributing to the growth of the data science team culture.