Data Science Analyst II
The University of Texas at Austin
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Job summary
The Data Science Analyst II at The University of Texas at Austin partners with clinicians and leaders to develop analytics, predictive models, and decision-support solutions that improve patient care and operational performance. The role emphasizes hands-on SQL, relational databases, and automated data pipelines for reliable, analysis-ready datasets.
Responsibilities include collaboration with data architects and clinical teams, building models, dashboards, and automated reports, and ensuring
Qualifications
- Master's degree plus 3+ years in data science, predictive analytics, ML, or healthcare analytics.
- Strong SQL, data modeling, and Python programming skills.
- ETL pipelines development and cloud platforms experience (Azure, AWS or Google Cloud).
- Authorized to work in the United States full-time without visa sponsorship.
Responsibilities
- Partner with clinicians and leaders to identify analytics opportunities.
- Design and deploy predictive models for clinical and operational use.
- Build automated ETL pipelines and ensure data quality.
- Develop dashboards and decision-support tools for stakeholders.
Skills
Education
Tools
Job description
Data Science Analyst II
Hiring Department: Dell Medical School
Position Open To: All Applicants
Weekly Scheduled Hours: 40
FLSA Status: Exempt from FLSA
Earliest Start Date: Immediately
Position Duration: Expected to Continue
Location: UT MAIN CAMPUS
The Data Science Analyst II partners with clinical, operational, and administrative leaders to develop advanced analytics, predictive models, and decision-support solutions that improve patient care, operational efficiency, and organizational performance.
A key focus of this position is building a reliable foundation for healthcare analytics by working directly with clinical databases and healthcare data to extract, integrate, clean, validate, and prepare accurate, analysis-ready datasets. Supporting the Department of Pediatrics, this role emphasizes hands-on SQL, relational databases, healthcare data structures, data integration, and automated data pipelines to ensure clinical and research teams have access to reliable information for reporting, operational decision-making, and future advanced analytics initiatives.
This role translates complex healthcare and business problems into scalable data science and machine learning solutions while collaborating closely with clinicians, researchers, informaticists, data engineers, and business stakeholders. The Data Science Analyst II develops predictive models, builds automated data pipelines, and delivers actionable insights that support enterprise decision-making and clinical innovation.
- Partner directly with clinicians, operational leaders, researchers, and administrative stakeholders to identify analytical opportunities that improve patient care and operational performance.
- Translate complex clinical and business questions into scalable analytical solutions.
- Present technical findings and recommendations to both technical and non-technical audiences.
- Serve as a trusted consultant on data science, predictive analytics, and AI initiatives.
- Design, develop, validate, and deploy predictive and machine learning models supporting clinical and operational initiatives.
- Perform feature engineering, model evaluation, hyperparameter tuning, and performance monitoring.
- Conduct forecasting, trend analysis, anomaly detection, and scenario modeling.
- Monitor deployed models for drift and recommend improvements as data changes.
- Translate analytical findings into actionable recommendations.
- Build and maintain automated ETL pipelines and reproducible analytical workflows.
- Integrate structured and unstructured data from multiple enterprise healthcare systems.
- Ensure data quality through validation, reconciliation, and testing.
- Partner with Data Engineering and IT teams to optimize data architecture and performance.
- Use SQL and relational database tools to extract, transform, reconcile, and organize healthcare data into reliable, reusable datasets for clinical, operational, and research analytics.
- Develop dashboards and interactive reporting tools that support operational and clinical decision-making.
- Automate recurring reports and analytical processes.
- Maintain consistency of KPIs and enterprise reporting standards.
- Create clear visualizations that simplify complex analytical findings.
- Lead small-to-medium analytics initiatives from planning through implementation.
- Define project milestones, manage priorities, and communicate status updates.
- Mentor junior analysts and promote data science best practices.
- Collaborate closely with data architects, engineers, informaticists, and clinical leaders to ensure successful implementation.
- Evaluate emerging AI, machine learning, and cloud technologies for enterprise adoption.
- Monitor model performance and coordinate remediation following data or regulatory changes.
- Ensure compliance with HIPAA, security standards, and institutional policies.
- Adhere to internal controls and reporting requirements.
- Perform related duties as assigned.
- Strong understanding of predictive analytics, statistics, and machine learning techniques.
- Proficiency in Python, SQL, and modern analytics frameworks.
- Experience developing automated ETL pipelines and maintaining data integrity.
- Experience working with cloud-based analytics environments.
- Ability to communicate technical concepts to clinical, operational, and executive audiences.
- Strong presentation and stakeholder engagement skills.
- Ability to translate complex analytical findings into actionable recommendations.
- Demonstrated ability to partner effectively with clinicians, researchers, operational leaders, and technical teams.
- Strong business acumen with a collaborative, solution-oriented approach.
- Ability to balance technical feasibility with operational priorities.
- Master's degree in Data Science, Statistics, Computer Science, Engineering, Health Informatics, or a related field, with at least three (3) years of professional experience in data science, predictive analytics, machine learning, or healthcare analytics.
- Experience applying data science and predictive analytics to solve healthcare, clinical, or business problems.
- Strong SQL, data modeling, and Python programming skills.
- Experience developing ETL pipelines and working with cloud platforms (Azure, AWS, or Google Cloud).
- Experience collaborating directly with business, operational, clinical, or research stakeholders to develop analytical solutions.
- Excellent written, verbal, and interpersonal communication skills.
- Relevant education and experience may be substituted as appropriate.
- Applicants must be authorized to work in the United States on a full-time basis without the need for current or future visa sponsorship.
- Doctorate in Data Science, Computer Science, Engineering, Statistics, Health Informatics, or related field.
- Five (5)+ years of applied machine learning or healthcare analytics experience.
- Experience supporting provider organizations, academic medical centers, hospitals, or integrated health systems.
- Experience working with provider-side healthcare data, clinical workflows, operational healthcare analytics, or population health initiatives.
- Experience working with healthcare datasets and interoperability standards such as OMOP, FHIR, or HL7.
- Experience operationalizing machine learning models using MLOps practices.
- Experience developing automated ETL pipelines and cloud-native analytics solutions.
$80,000+ depending on qualifications.
- Standard office equipment.
- Repetitive use of a keyboard.
- May be exposed to such occupational hazards as communicable diseases, blood borne pathogens, ionizing and non-ionizing radiation, hazardous medications and disoriented or combative patients, or others.
- Resume/CV
- 3 work references with their contact information; at least one reference should be from a supervisor
- Letter of interest
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Regular staff who have been employed in their current position for the last six continuous months are eligible for openings being recruited for through University-Wide or Open Recruiting, to include both promotional opportunities and lateral transfers. Staff who are promotion/transfer eligible may apply for positions without supervisor approval.
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length.
A criminal history background check will be required for finalist(s) under consideration for this position.
The University of Texas at Austin, as an equal opportunity/affirmative action employer,complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.
The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information.
If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in loss of employment at the university.
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The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university's company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following:
- E-Verify Poster (English and Spanish) [PDF]
- Right to Work Poster (English) [PDF]
- Right to Work Poster (Spanish) [PDF]
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Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031.
The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.
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