Okay, I've searched for full-time Data Scientist roles in Salt Lake City, UT, requiring 6 years of experience, a Bachelor's degree in a quantitative field, and proficiency in Python. I have found 57 positions for you.

Sure. Here's the analysis:

Job Analysis:

The Data Scientist role at the University of Utah Health Sciences Strategy team is fundamentally about harnessing complex, diverse datasets to advance strategic decision-making within a large academic health system. The position exists to translate raw, often messy data into actionable insights that shape health system initiatives including patient segmentation, cost modeling, and market analysis. Responsibilities extend beyond pure number crunching to storytelling, visualization, and clear communication tailored for both clinical and executive stakeholders. The emphasis on collaboration and adaptability highlights the dynamic nature of healthcare analytics, where swift shifts in priorities and multi-disciplinary teamwork are the norm. The required skills—proficiency in programming languages like Python or R, statistical and machine learning methods, SQL, and dashboard tools—equip the candidate to manage and interpret heterogeneous data sources effectively. Meanwhile, soft skills such as curiosity, proactive engagement, communication, and managing multiple deadlines enable one to thrive amid competing demands and evolving strategic goals. Success in this role involves not only technical mastery but also the ability to work as a trusted internal consultant while contributing to broader organizational learning and innovation. Given the healthcare environment, the candidate must also be comfortable with the regulatory and operational nuances influencing data availability and interpretation. The presence of a senior data scientist and executive director as supervisors suggests that this role combines independent project ownership with close mentorship and strategic alignment. A candidate able to demonstrate flexibility, technical rigor, and storytelling prowess will likely produce impactful analyses that directly influence health system strategy within their first year.

Company Analysis:

The University of Utah Health Sciences is a prestigious and mission-driven academic health system operating at the intersection of medical education, research, and patient care. Positioned as a stable yet innovative institution, it demands roles that blend rigorous expertise with a sensitivity to the complex environment of healthcare delivery and academic priorities. The commitment to diversity, inclusion, and equal opportunity reflects a culture that values collaboration and broad representation. This setting suggests a work environment that balances structured processes with the need for agility, especially in strategic analytics to keep pace with healthcare trends. The Data Scientist role’s place within the Health Sciences Strategy team implies a high visibility function that interacts with multiple university entities, requiring an ability to navigate academic bureaucracy and foster cross-functional relationships. The hybrid work schedule blending campus presence and downtown office days indicates a strong emphasis on collaboration and presence among clinical and administrative partners, reinforcing that relationship-building is critical. Given that the University is a large institution, the role likely affords exposure to senior leadership while demanding the ability to translate technical analytics into language and visuals accessible to non-technical executives. Strategically, this hire appears to support ongoing efforts to leverage data for health system optimization — a growth and innovation focus area — and thus aligns with broader institutional goals of advancing healthcare outcomes, operational efficiency, and academic excellence. A candidate who appreciates the mission-driven context and demonstrates both technical agility and interpersonal savvy will find strong opportunities for professional growth and meaningful impact here.

Absolutely. Here are some mock interview questions that could come up:

• Behavioral: Tell me about a time when you had to clean and analyze a large, complex dataset with incomplete or inconsistent data. How did you approach the task and what was the outcome?
• Behavioral: Describe a situation where you collaborated with non-technical stakeholders (such as clinicians or business leaders) to deliver a data-driven insight. How did you ensure your communication was clear and actionable?
• Behavioral: Can you share an example of a project where you managed multiple competing priorities and tight deadlines? How did you maintain quality and timely delivery?
• Behavioral: Discuss a time when you received critical feedback from a colleague or manager on your analysis or code. How did you respond and what did you learn?
• Technical: Explain how you would design a patient segmentation model using a heterogeneous healthcare dataset. What techniques and tools would you employ?
• Technical: How have you utilized machine learning methods, such as supervised or unsupervised techniques, to solve a business or clinical problem? Provide a specific example.
• Technical: Walk us through your experience with creating dashboards or interactive visualizations. Which tools have you used, and how did you ensure these visualizations supported user learning and decision-making?
• Technical: Describe your proficiency with SQL in data wrangling and extraction. Can you give an example of a complex query you wrote and how it supported an analytics project?
• Situational: Imagine a senior leader asks for an urgent analysis on cost drivers influencing a hospital department’s budget, but the data available is fragmented and inconsistent. How would you approach this challenge?
• Situational: You are working on a project where clinical partners disagree on the interpretation of your data findings. How would you navigate this conflict and reach consensus?
• Situational: You have multiple simultaneous projects with shifting priorities. How do you decide which tasks to focus on and how do you communicate progress to your manager and stakeholders?
• Company Fit/Motivation: Why are you particularly interested in joining the University of Utah Health Sciences Strategy team as a Data Scientist?
• Company Fit/Motivation: How do your personal values and career goals align with the mission of an academic health system focused on improving healthcare and education access?
• Company Fit/Motivation: The University emphasizes collaboration across teams and disciplines. How do you cultivate effective teamwork in a cross-functional environment?
• Candidate Questions: Can you describe how the Health Sciences Strategy team measures success for data science projects?
• Candidate Questions: How does the team stay current with emerging data science methods and tools, and are there opportunities for professional development?
• Candidate Questions: What is the typical collaboration process like between Data Scientists and clinical or operational leaders here at the University?