Job Description

This role is responsible for leveraging your expertise in data analytics, advanced statistical methods, and programming to derive insights from clinical data. As a member of the Enterprise Data Science team, this role will be responsible for analyzing Patient Experience (PX) data, nursing operations outcomes and other complex clinical datasets, developing data visualizations and dashboards, assisting with data model and/or feature development, and translating insights into actionable recommendations for improving PX and nursing operations across the enterprise.

Essential Functions

• Collaborate with cross-functional teams including nursing and other clinical leaders, data scientists, and software engineers to identify data-driven opportunities for enhancing clinical processes and patient care.
• Utilize cloud-based technologies, such as Google Cloud Platform (GCP), for scalable data processing and analysis.
• Manage and visualize HCAHPS "Top Box" performance across all domains, including providing early-warning alerts for units trending below benchmarks and identify drivers of success in high-performing areas, and implementing best practices for data management, including data quality assessment and data validation.
• Lead the effort to merge patient experience data with HR data (turnover/burnout) and Clinical data (falls/pressure ulcers) to provide a 360-degree view of nursing excellence.
• Utilize Python programming and associated libraries such as PyTorch, Keras, Pandas and NumPY to create, train, test and implement meaningful data science models.
• Apply Natural Language Processing (NLP) to transform qualitative patient feedback into structured insights, categorizing thousands of patient comments into specific, actionable nursing interventions.
• Lead the analysis of nursing operational data to identify patterns, trends, and correlations relevant to healthcare outcomes.
• Collaborate with healthcare professionals and domain experts to understand operational needs and design data-driven solutions.
• Design and conduct experiments, interpret results, and communicate findings to both technical and non-technical stakeholders
  

Qualifications

• Master's degree in Data Science, Data Analytics, Computer Science, or a related field.
• Proficiency in Python programming and associated libraries.
• Experience with cloud-based platforms such as Google Cloud Platform (GCP) for data storage, processing, and deployment.
• 2–4 years of experience in healthcare analytics, specifically working with PX metrics and nursing operations outcome data.
• Deep understanding of HCAHPS domains, CMS Value-Based Purchasing (VBP) requirements, and the financial impact of patient experience scores on hospital reimbursement.
• Strong grasp of psychometrics and survey design to ensure accurate interpretation of patient feedback and response rates.
• History of translating ambiguous business questions into rigorous SQL logic.
• Proficiency Advanced proficiency in modern visualization suites (e.g., Tableau, Power BI, Looker) and programmatic libraries (e.g., Matplotlib, Seaborn, Plotly), with demonstrated experience creating interactive executive dashboards to granular technical deep dives.
• Excellent communication and presentation skills with the ability to translate technical concepts to non-technical audiences.