You will develop frameworks to quantify the ROI and performance of AI/ML projects across healthcare domains.
Responsibilities
Develop standardized frameworks to track ROI and establish baselines, targets, and monitoring processes for AI/ML investments.
Construct and maintain performance dashboards to monitor model accuracy, precision, recall, and operational metrics like cost savings and patient outcomes.
Build production-level code using Python and SQL for data exploration, cleaning, and transformation across EHR and claims data.
Partner with clinicians, IT professionals, and executives to identify high-impact AI/ML use cases and communicate technical findings to non-technical stakeholders.
Collaborate with software engineering teams to implement model retraining, adjustments, and fixes.
Required Skills
5+ years of experience in data science or a related quantitative field.
Expertise in Python and SQL for data manipulation and statistical analysis.
Proficiency in machine learning algorithms, statistical modeling, and performance evaluation.
Experience building dashboards using Tableau or Looker Studio.
Familiarity with electronic health records (EHR) systems and healthcare data structures.
Knowledge of HIPAA and healthcare metrics such as readmission rates and length of stay.
Proven ability to design and track ROI metrics for AI/ML initiatives.
Bachelor’s degree in Computer Science, Data Science, Statistics, or a related quantitative field.
Preferred Skills
Master’s degree or PhD in Data Science or Biomedical Informatics.
Experience with Google Cloud Platform, git, GitHub, and Docker.