Senior Data Analyst

utaustin; Austin (TX); On-site; USD 110,000 - 140,000; Full time

Job summary

University of Texas at Austin seeks a Senior Data Analyst to lead complex data analytics initiatives across clinical, operational, and financial domains within the UT Data Core and the Department of Women's Health. You will extract, transform, and interpret data from diverse sources to deliver high-impact insights.

Collaborating with leadership, faculty, and cross-functional teams, you will build predictive models, dashboards, and data standards that inform strategic decisions and drive

Qualifications

• Analyses data using standard statistical tools, methods, and techniques.
• Translates business problems into analytical frameworks.
• Presents findings to senior leaders and governance committees.
• Collaborates with clinical, IT, and administrative teams to scope data needs.
• Stays current with analytics trends and new methodologies.

Responsibilities

• Lead strategic data analysis and modeling to support clinical, operational, and financial decision-making.
• Develop and maintain dashboards and standardized KPIs across departments.
• Lead integration of disparate data sources including EHR, claims, financial, and operational systems.
• Provide guidance to leadership and stakeholders on data requirements and interpretations.
• Mentor junior analysts and document analytic processes.
• Drive innovation and evaluate new analytics tools and methodologies.

Skills

Strategic Agility

Dealing with Ambiguity

Influence

Technical Learning

Innovation Management

Job description

Job Posting Title

Senior Data Analyst

Hiring Department

Department of Women's Health

Position Open To

All Applicants

Weekly Scheduled Hours

40

FLSA Status

Exempt from FLSA

Earliest Start Date

Immediately

Position Duration

Expected to Continue

Location

AUSTIN, TX

Job Details

General Notes The Senior Data Analyst is a senior-level individual contributor responsible for leading complex data analytics initiatives that drive strategic decision-making across clinical, operational, and financial domains. This position is housed within the UT Data Core team and works directly with the Department of Women's Health to support departmental projects, analytics initiatives, and data requests. The role partners closely with leadership, clinical program directors, faculty, staff, and cross-functional teams to deliver high-impact insights and data-driven solutions. The Senior Data Analyst serves as a subject matter expert in healthcare data, advanced analytics, and data visualization, with expertise in extracting, integrating, analyzing, and interpreting data from electronic health records (EHRs) and other clinical and operational data sources. The position utilizes Viewpoint and other relevant data systems and reporting tools to fulfill complex data requests and support clinical, research, operational, and strategic initiatives within Women's Health.

Responsibilities

Strategic Data Analysis and Modeling

• Analyzes data using standard statistical tools, methods, and techniques; interprets results to identify significant differences and trends.
• Leads the design and execution of advanced statistical models and predictive analytics.
• Translates complex business problems into analytical frameworks.
• Synthesizes, processes, and analyzes large datasets to uncover actionable insights.
• Presents findings to senior leadership and governance committees.

Data Visualization

• Develops and maintains dashboards and scorecards.
• Standardizes KPIs and reporting methodologies across departments.
• Automates enterprise-level reporting processes.
• Ensures data visualizations are intuitive, accurate, and aligned with strategic goals.
• Collaborates with IT to optimize reporting infrastructure.

Data Integration, Architecture and Standards

• Develops and implements databases, data collection systems, and analytics strategies that optimize statistical efficiency and data quality.
• Leads integration of disparate data sources including EHR, claims, financial, and operational systems.
• Assists in defining, developing, and implementing data standards and data quality measures.
• Conceptualizes, creates, and maintains operational and research data models for visualization and statistical analysis.
• Establishes and maintains standard work procedures governing the appropriate use of data.

Stakeholder Leadership and Consultation

• Serves as a trusted advisor to clinical and administrative leaders.
• Consults with internal and external customers, including faculty and staff, to identify user needs and clarify data requirements.
• Provides guidance and interpretation of complex systems and data.
• Facilitates data strategy sessions and requirements gathering workshops.
• Builds consensus around data definitions and usage.

Mentorship, Documentation, and Innovation

• Mentors junior and mid-level analysts on technical and professional development.
• Documents data analysis efforts, including data sources, reporting specifications, tools used, and issue resolutions.
• Evaluates and pilots emerging analytics tools and methodologies.
• Researches and stays up-to-date on new technologies and data analysis trends.
• Leads analytics communities of practice and training sessions.
• Contributes to scholarly activity.

Marginal or Periodic Functions

• Participates in strategic planning and digital transformation initiatives.
• Supports grant-funded research and academic collaborations.
• Represents the organization at industry conferences and professional forums.
• Leads post-implementation reviews of analytics projects.
• Contributes to vendor evaluations and procurement of analytics tools.

Knowledge/Skills/Abilities

Strategic Agility

• Aligns analytics with long-term organizational goals.
• Anticipates data needs for emerging initiatives.
• Advises leadership on strategic risks and opportunities.

Dealing with Ambiguity

• Navigates unclear or evolving data requirements.
• Makes sound decisions with incomplete information.
• Adapts analysis to shifting priorities.

Influence

• Builds consensus around data-driven decisions.
• Communicates complex findings to diverse audiences.
• Gains buy-in for analytics initiatives.

Technical Learning

• Masters new analytics tools and platforms.
• Applies advanced statistical and machine learning techniques.
• Stays current with industry trends.

Innovation Management

• Pilots new technologies for data processing, data generation (e.g. Synthetic), and analysis.
• Encourages experimentation and learning.
• Identifies opportunities for automation and AI.

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