Designs and develops predictive models using advanced ML methods.
Performs feature engineering, model evaluation, and hyperparameter tuning.
Builds and tests prototypes for deployment in clinical or operational workflows.
Conducts scenario modeling, pattern detection, and trend forecasting.
Monitors models for performance and drift
Synthesizes findings into meaningful insights and recommendations.
Data Integration and Pipeline Development
Integrates structured and unstructured data from multiple enterprise systems.
Builds and maintains automated pipelines, ETL processes, and reproducible scripts.
Uses code repositories and CI/CD methods for model and analytics deployment.
Ensures data accuracy through validation and rigorous quality checks.
Partners with IT and data engineering to optimize architecture.
Data Visualization and Decision Support
Develops advanced dashboards and interactive tools.
Automates recurring modeling outputs and analytics workflows.
Ensures consistency of model-driven KPIs across departments.
Creates visualizations that simplify complex findings.
Stakeholder Engagement and Consultation
Serves as a data science consultant to clinical and operational leaders.
Translates ambiguous questions into structured analytical methods.
Leads meetings to gather requirements and present insights.
Guides teams on the interpretation of AI/ML outputs.
Mentorship and Project Leadership
Mentors junior analysts and reviews modeling work.
Leads small-to-medium-sized data science projects.
Defines milestones, tracks progress, and communicates with stakeholders.
Contributes to the development of data science best practices.
Marginal or Periodic Functions:
Evaluates emerging AI/ML tools and cloud technologies to guide enterprise adoption and architecture decisions.
Ensures data science workflows comply with security, HIPAA, and institutional standards through periodic reviews.
Audits and remediates model performance after drift, regulatory changes, or major data-source updates to maintain safe clinical integration..
Adheres to internal controls and reporting structure.
Performs related duties as required.
Knowledge/Skills/Abilities:
Functional/Technical Skills
Demonstrates a strong understanding of advanced statistical and ML techniques.
Applies advanced ML/statistical methods to build predictive models.
Maintains proficiency in Python, SQL, and ML frameworks.
Ensures data integrity across complex pipelines and ETL processes.
Priority Setting
Possesses the ability to manage complex analytical workflows and multiple priorities.
Balances multiple analytics projects and deadlines effectively.
Allocates resources to high-impact modeling initiatives.
Adjusts priorities when urgent clinical needs arise.
Communicating Effectively
Communicates effectively and simplifies technical concepts.
Translates technical findings into actionable insights for leaders.
Creates visualizations that make complex data understandable.
Adapts communication style for technical and non-technical audiences.
Technical Learning
Demonstrates proficiency in cloud-based analytics environments.
Adopts emerging cloud tools and MLOps practices.
Experiments with new ML algorithms and evaluates performance.
Shares new techniques with peers through code reviews and demos.
Peer Relationships
Exhibits a collaborative mindset with strong business acumen.
Partners with IT, clinicians, and administrators on data projects.
Resolves conflicts between technical feasibility and operational needs.
Encourages team knowledge-sharing and joint problem-solving.
Required Qualifications
Requires a Master's Degree in Data Science, Engineering, Statistics, Computer Science, or related field with at least 3 year(s) of experience in data science, machine learning, or predictive analytics.
Proficiency in Python or similar language
Strong SQL and data modeling skills.
Experience with cloud platforms (Azure, AWS, Google).
Familiarity with
Additional Information
Job Posting Title:
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 ----
Job Details:
Purpose
The Data Science Analyst II is responsible for developing and deploying advanced analytics, machine learning models, and data pipelines to support enterprise and clinical decision‑making. This role partners with clinical and administrative leaders to translate complex business problems into scalable data science and AI solutions, contributes to predictive modeling and automation initiatives, and mentors junior analysts. Working closely with data architects, engineers, informaticians, and clinicians, the Data Science Analyst II helps design and implement innovative analytic solutions-often at the point of care-that drive systemwide performance improvement.
Utaustin · UT Main Campus