Data Scientist, Senior

Overview

As a patient-focused organization, University of Utah Health exists to enhance the health and well-being of people through patient care, research and education. Success in this mission requires a culture of collaboration, excellence, leadership and respect. University of Utah Health seeks staff that are committed to the values of compassion, collaboration, innovation, responsibility, integrity, quality and trust that are integral to our mission.

EO/AA

The Senior Data Scientist partners closely with leadership to solve the organization’s most technically challenging and high-impact problems across clinical and operational domains. They bring deep expertise in the data science lifecycle and healthcare/business context to create impactful solutions. Within the Data Science team, they set technical standards, provide mentorship and rigorous review, and strengthen shared practices to improve the quality and consistency of the team’s work.

Corporate Overview:
University of Utah Health is an integrated academic healthcare system with five hospitals including a level 1 trauma center, eleven community health centers, over 1,600 providers, and a health plan serving over 200,000 members. University of Utah Health is nationally ranked and recognized for our academic research, quality standards and overall patient experience. In addition to our clinical delivery system, we have a School of Medicine, School of Dentistry, College of Nursing, College of Pharmacy, and College of Health providing education and training for over 1,250 providers annually.

We have over 2 million patient visits annually and research grants exceeding $350 million. University of Utah Hospitals and Clinics represents our clinical operations for the larger health system.

• Serve as a team expert in one or more technical domains (e.g., biostatistics, machine learning, NLP ) and apply advanced methods to solve complex problems.
• Lead project framing, modeling strategy, experiment design, and deployment planning through independent execution.
• Define and uphold analytic and engineering standards for scalable pipelines, model deployment, monitoring, and lifecycle management in partnership with engineering and IT.
• Implement reproducible, well‑structured code in Python/R and SQL, establishing team‑wide conventions where appropriate.
• Acquire, clean, transform, validate, and explore data from multiple systems using repeatable processes to identify patterns and anomalies.
• Evaluate and introduce new tools, methods, or approaches when they provide clear value to the team or organization.
• Document data sources, assumptions, analytic steps, methodologies, and limitations with clarity and accuracy.
• Communicate findings and recommendations through concise summaries and presentations tailored to stakeholders.
• Provide mentorship and thought partnership through design reviews and collaborative problem‑solving.
• Collaborate with data scientists, analysts, and cross‑functional partners to integrate analytic work into operational workflows.
• Follow HIPAA, PHI, and data governance protocols.
• Perform additional work as needed to support team success.

• Mastery of SQL and Python or R.
• Insatiable curiosity.
• Deep understanding of data science methods, with the ability to use or adapt them in novel and rigorous ways.
• Expert knowledge of ML deployment and monitoring best practices.
• Knowledge of nuances of EHR and hospital operations data.
• Ability to clearly explain model results, uncertainty, and analytic rationale to both technical and non‑technical partners.
• Strong project leadership skills, including managing multiple ambiguous, technically challenging initiatives and aligning stakeholders.
• Ability to…