Senior Data Science Analyst

University of Texas at Austin•Austin, TX

1d•$101,500•Onsite

About The Position

The Senior Data Science Analyst is a senior-level expert responsible for leading enterprise-wide data science initiatives that advance clinical care, operational efficiency, and innovation. Reporting to the Chief Data Officer (CDO) or other departmental leader, this role designs and deploys complex statistical and machine learning models, oversees data architecture improvements, and serves as a trusted advisor to organizational leadership. The Senior Data Science Analyst mentors data science staff, guides strategic analytics decisions, and leads the development of advanced data capabilities across the institution.

Requirements

Requires a Master's Degree in Data Science, Engineering, Statistics, Computer Science, or a related analytical/quantitative field with at least 5 year(s) of experience in advanced analytics or data science.
Expertise in cloud analytics environments and ML frameworks.
Experience with healthcare data standards (OMOP, FHIR, DICOM).
Skilled in large-scale data processing, modeling, and architecture design.
Demonstrates strong strategic thinking and has the ability to navigate ambiguous environments.
Connects analytics roadmap to institutional goals and future capabilities.
Frames enterprise analytics choices with clear criteria and risk/benefit analysis.
Exhibits expertise in ML, AI, and advanced statistical modeling.
Selects and implements appropriate ML architectures aligned to problem constraints.
Designs robust data models and pipelines with reproducibility and monitoring.
Maintains a continuous learning and innovation mindset.
Triages model performance anomalies with root cause analysis and corrective actions.
Integrates different data sources to address complex, multi factor questions.
Provides leadership in cross-functional teams and enterprise initiatives.
Builds cross functional alignment on definitions and KPIs.
Navigates governance bodies to advance responsible AI/ML adoption.
Communicates at a high level with messaging tailored to executive audiences.
Crafts executive level narratives linking insights to operational decisions.
Builds dashboards and scorecards that reveal trends and actionable thresholds.

Nice To Haves

Doctorate in Engineering, Mathematics, Computer Science, Health Science, Data Science, Statistics, or a related analytical/quantitative field with at least 3 year(s) of experience in a complex healthcare setting.
Published research or presentations at professional conferences.
Demonstrated experience in ETL, automation, and at least one cloud environment.
Experience with clinical informatics data exchange standards and platforms is also desirable.
Relevant education and experience may be substituted as appropriate.

Responsibilities

Leads the development of advanced ML and AI models, including deep learning and natural language processing.
Oversees the design of analytical frameworks for organization-wide initiatives.
Interprets findings for executive and governance audiences.
Implements scalable model architectures and optimization strategies.
Advises leadership on risks, opportunities, and emerging technologies.
Leads the integration of heterogeneous data sources across the enterprise.
Designs data architectures supporting advanced modeling and analytics.
Develops and enforces data standards, quality measures, and governance.
Creates robust data models for research, predictive analytics, and operational use.
Partners with IT to optimize cloud infrastructure and MLOps solutions.
Creates enterprise-level dashboards, scorecards, and reporting methodologies.
Standardizes KPIs across clinical and operational domains.
Leads automation of recurring analytics and model-driven insights.
Advises senior executives, clinical leaders, and program directors.
Leads requirements workshops and data strategy sessions.
Builds consensus on model adoption, data definitions, and governance.
Represents the analytics program at committees and external forums.
Mentors junior and intermediate analysts in advanced analytics techniques.
Documents analytical frameworks, data sources, and methodological decisions.
Leads pilots of emerging AI/ML tools, including synthetic data and automation.
Contributes to research collaborations, publications, and scholarly activity.
Conducts periodic audits of data quality and governance standards.
Evaluates emerging AI/ML tools through short pilots and reports findings.
Facilitates executive briefings on strategic analytics initiatives.
Adheres to internal controls and reporting structure.
Performs related duties as required.