Location: Dallas, TX (Hybrid On-Site)
Education: PhD preferred
Our healthcare client is seeking a Principal Data Scientist to lead advanced analytics, AI/ML solutions, and clinical decision-support initiatives using a modern health-system data stack: Epic (Clarity/Caboodle), Azure, Databricks, Spark, MLflow, Python/R, and Power BI. This role drives high-impact modeling that improves patient outcomes, operational efficiency, and population health.
Key Responsibilities
- Lead strategy and execution of AI/ML initiatives for clinical and operational innovation.
- Build, deploy, and optimize predictive models using Databricks, Spark, MLflow, and Azure pipelines.
- Partner with clinicians and healthcare leaders to translate problems into actionable insights.
- Collaborate with data engineering teams to enhance pipelines from Epic Clarity/Caboodle into Azure Data Lake.
- Ensure models meet standards for quality, fairness, explainability, and HIPAA compliance.
Qualifications
- PhD in Data Science, Computer Science, Biomedical Informatics, Statistics, Engineering, or related field.
- 8+ years of experience in data science/ML (healthcare strongly preferred).
- Expert in Python/R, Spark, Databricks, MLflow, and cloud ML deployment (Azure).
- Strong knowledge of EHR data, healthcare data structures, and clinical workflows.
- Proven leadership, communication, and cross-functional collaboration skills.
Preferred
- Experience integrating predictive models into Epic or clinical workflows.
- Background in NLP, time-series, causal inference, or population health analytics.