Senior Business Intelligence Manager

Mayo Clinic•Rochester, MN

4d•$112,000 - $157,900

About The Position

Plays a critical role supporting the advancement of analytics and data science activities of Mayo Clinic. Collaborates closely with the 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.

Requirements

High order analytics and business expertise
World-class data science, analytical tools and approaches
Statistical modeling of behaviors, propensities and affinities
Sentiment analysis for a topic or interest
AI, machine learning, decision trees, clustering, pattern recognition, and other data science approaches
Self-service tools and dashboards
Integration of external data
Decision support
Data-driven strategies and tactics development
Data architecture input

Responsibilities

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.