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Senior Data Analyst

UNIVERSITY OF TEXAS AT AUSTIN

Austin, TXJobSeen 5 days agoSeen in employer's feed 5 days ago

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At a glance

Compensation
No compensation found
Location
Austin, TX
Work Authorization
Not specified

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Job overview

The Senior Data Analyst leads advanced statistical modeling, predictive analytics, and analysis of large datasets to inform organizational decisions. The role develops dashboards, reporting standards, and data infrastructure; integrates clinical, financial, and operational sources; and advises leaders and stakeholders on data strategy. It also mentors analysts, evaluates emerging tools, supports research, and contributes to enterprise analytics initiatives.

Skills & qualifications

RequiredNice to have

Skills

Statistical AnalysisPredictive AnalyticsData VisualizationDashboard DevelopmentKPI StandardizationReporting AutomationDatabase DevelopmentData IntegrationData ModelingData Quality ManagementMachine LearningData StrategyStakeholder ConsultationConsensus BuildingCommunicationMentoringCross-Functional LeadershipAdaptabilityDecision-MakingInnovation Management

Full job description

Strategic Data Analysis and ModelingAnalyzes 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 VisualizationDevelops 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 StandardsDevelops 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 ConsultationServes 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 InnovationMentors 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 FunctionsParticipates 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/AbilitiesStrategic AgilityAligns analytics with long-term organizational goals.Anticipates data needs for emerging initiatives.Advises leadership on strategic risks and opportunities.Dealing with AmbiguityNavigates unclear or evolving data requirements.Makes sound decisions with incomplete information.Adapts analysis to shifting priorities.InfluenceBuilds consensus around data-driven decisions.Communicates complex findings to diverse audiences.Gains buy-in for analytics initiatives.Technical LearningMasters new analytics tools and platforms.Applies advanced statistical and machine learning techniques.Stays current with industry trends.Innovation ManagementPilots new technologies for data processing, data generation (e.g. Synthetic), and analysis.Encourages experimentation and learning.Identifies opportunities for automation and AI.CollaborationLeads cross-functional analytics teams.Shares knowledge and builds analytics capacity.Supports enterprise-wide data initiatives.

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