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# Senior Business Intelligence Manager

- **Company:** Mayo Clinic
- **Location:** Rochester, MN, United States
- **Experience:** Expert
- **Salary:** $112,000.0 - $157,900.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Clinical Data Repository, Cloud Computing, Cluster Analysis, Databases, Data Architecture, Data Validation, Data Visualization, Decision Support Systems, Machine Learning, Marketing Information Systems, Pattern Recognition, SQL Databases, Tableau (Software), Information Technology, Data Analytics
- **Published:** August 9, 2026
- **Apply:** https://www.adzuna.com/details/5779149958

## About the Role

Master's degree in Engineering Science, Management Information Systems, or related and 6 years of experience required.

Skills:

Relational (SQL), Cloud Oriented Databases; Experience with Tableau and other visualization tools to create self-service tools and dashboards;

Experience with data validation tests and QA testing;

Collecting data from multiple sources;

Integration of external data into existing ecosystem of prospect insights tools;

Conducting statistical analysis using packing in R & Python programming language;

Leveraging data science approaches including AI, machine learning, decision trees, clustering, and pattern recognition;

Experience with various types of data (marketing data including digital, CRM and clinical data).

## Description

Plays critical role supporting advancement of analytics and data science activities of Mayo Clinic. Collaborates closely with Marketing team (including direct), Information Technology

functional experts, and others as needed. Acts as an internal consultant by applying high order analytics and business expertise to Mayo Clinic's Departments. Assists with creating business insights through world-class data science, analytical tools and approaches. Identifies insights on prospects' behaviors, financial performance, trends of giving, affinities and use of departmental resources. This includes, but it is not limited to: Statistical modeling of behaviors, propensities and affinities, as well as sentiment for a topic or interest (leveraging AI, machine learning, decision trees, clustering, pattern recognition, and other data science approaches). Self-service tools and dashboards supporting functional areas of department. Integration of external data into existing ecosystem of prospect insights tools. Decision support for functional areas of department. Analysis supporting data-driven strategies and tactics development. Input into data architecture supporting future and current
needs. Other ad hoc analysis as needed.


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