Analytics Advisor-Hybrid
Listed on 2026-10-16
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IT/Tech
Data Analyst, Data Science Manager, AI Engineer (Applied/Software), Data Engineering
HYBRID: This is a hybrid position and must be located within 100 miles of any of the Mayo Clinic campuses for on-site expectations based on business needs.
This individual contributor role offers a unique opportunity to help shape the future of Finance analytics by pairing trusted data with modern analytical and AI capabilities. Approximately 40% of the role will focus on traditional data production support-monitoring critical Finance data, improving quality and reliability, and helping ensure our data delivered each to our customers. The remaining 60% will focus on hands-on analytics delivery, building innovative solutions such as advanced analytics, conversational data experiences, and AI-enabled insights that help Finance answer more complex questions faster.
This role will require leveraging the latest tools in this space, include AI coding assistants for analytics development in Microsoft Fabric and Google Cloud.
Success in this role will require familiarity with and the ability to guide analytics projects through all analytics project stages:
Business Understanding, Data Understanding, Data Acquisition and Preparation, Visualization/Model Development, Deployment, Maintenance, and Retirement. Preference will be given to candidates with healthcare analytics experience.
The successful candidate must be able to bring data analytics projects to successful conclusion by performing analytics solution development as well as guiding fellow team members on task completion. The ability to exercise good judgement on when to discontinue analytic projects is also essential.
Key responsibilities for this role include:
- Designing visual solutions for storytelling using end user visualization tools
- Lead or advise small to medium analytics projects through all project stages
- Collaborate with other internal Data and Analytics teams to accelerate solution development
- Document solutions appropriately for handoff to supporting areas
- Establish and follow best practices related to data analytics and visualization
- Train and mentor staff on how to develop analytics and visualization solutions
- Acquire and transform data to optimize for analytics and visualization
- Build, optimize, and maintain analytical models
- Automate and develop reusable, self-service analytical tools and reports
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