University of Utah Health

Principal Data Scientist

Requisition Number
82379
Reg/Temp
Regular
Employment Type
Full-Time
Shift
Day
Work Schedule
M-F
Clinical/Non-Clinical Status
Non-Clinical
Location Name
University of Utah Campus
Workplace Set Up
Hybrid
City
Salt Lake City
State
UT
Department
COR AFF 98A SVP OFFICE TRNSFRS
Category
Information Technology

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.

 

The Principal Data Scientists leverage their expertise to analyze complex medical datasets—including (but not limited to) EHRs, genomics, and imaging to advance research, improve patient outcomes, and optimize clinical and business operations.

You will be part of the Innovation Office, a product factory inside the health system of the University of Utah.

 

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

Responsibilities

  • Develop predictive algorithms, run statistical models, and create data visualizations in close collaboration with clinicians and researchers.
  • Conducting hypothesis testing on large-scale structured and unstructured data, building AI/ML models.
  • Managing data pipelines to integrate fragmented clinical sources into actionable insights.
  • Work closely with stakeholders in product management, engineering, and operations teams to define performance goals, KPIs, and other success measurements.
  • Act as a thought partner to produce insights and metrics for various technical and business stakeholders across the teams.
  • Deliver effective presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.
  • Collaborate with the engineering team to ensure infrastructure supports key analyses.
  • Make business recommendations (e.g., cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.

Knowledge / Skills / Abilities

  • Expertise in data science or health informatics.
  • Technical proficiency in Python, R, and SQL.
  • Expertise in machine learning and data mining.
  • Firm grasp of medical terminology and HIPAA/data governance standards.
  • Innovative mindset with a keen eye for identifying opportunities for improvement.
  • Ability to thrive in a fast-paced, dynamic environment and simultaneously handle multiple projects.

Qualifications

Qualifications

Required

  • Bachelor’s degree in a relevant field.
  • 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL)
  • Experience in extracting data with SQL and designing ETL flows, and with statistical software (e.g., R, Python) and database languages (e.g., SQL).

Qualifications (Preferred)

Preferred

  • Experience working in complex academic medical center environments.
  • Experience with lifecycle management in a fast-paced software environment.
  • Ability to formulate data-driven proposals and excellent project management, problem-solving and leadership skills.
  • Experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling method.
  • Ability to teach others and learn new techniques such as differential privacy.
  • Experience with machine learning on large datasets.
  • Experience working with ServiceNow or JIRA.
  • Experience in large-scale data platforms.

Working Conditions and Physical Demands

Employee must be able to meet the following requirements with or without an accommodation.

  • This is a sedentary position in an office setting that may exert up to 10 pounds and may lift, carry, push, pull, or otherwise move objects. This position involves sitting most of the time and is not exposed to adverse environmental conditions.

Physical Requirements

Listening, Manual Dexterity, Near Vision, Sitting, Speaking, Standing

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