Principal Healthcare Data Analytics Leader

The University of Texas at Austin; Austin (TX); On-site; USD 115,000 - 150,000; Full time

Job summary

The University of Texas at Austin seeks a Principal Data Analyst to serve as a senior analytics expert, partnering with executive leadership to drive enterprise-wide analytics initiatives. This role focuses on healthcare analytics, predictive modeling, and AI-driven insights to influence clinical, operational, and financial outcomes.

You will lead the design of scalable data pipelines, governance, and analytics programs, ensuring data integrity and impactful decision support across multiple

Qualifications

• Requires a strong background in healthcare analytics and data science.
• Experience leading enterprise analytics projects and strategy.
• Expertise in predictive modeling, ML, and AI-driven analytics.
• Ability to translate complex data into actionable business insights.

Responsibilities

• Develop and govern enterprise analytics strategies across programs.
• Lead design and implementation of advanced predictive and prescriptive models.
• Partner with executive leadership to align analytics with priorities.
• Oversee data architecture, governance, and multi-source data integration.
• Communicate findings clearly to senior stakeholders and drive decisions.

Skills

Healthcare analytics

Data science

Predictive modeling

Machine learning

AI-driven analytics

Education

Bachelor's degree in Data Science/Statistics/CS/Public Health

Master's or PhD in quantitative/healthcare discipline

Tools

Azure

AWS

Google Cloud

Job description

The University of Texas at Austin seeks a Principal Data Analyst to serve as a senior analytics expert, partnering with executive leadership to drive enterprise-wide analytics initiatives. This role focuses on healthcare analytics, predictive modeling, and AI-driven insights to influence clinical, operational, and financial outcomes.

You will lead the design of scalable data pipelines, governance, and analytics programs, ensuring data integrity and impactful decision support across multiple