The primary purpose of this role is to perform hands-on analysis and serve as the point of contact for the data needs of Mayo Clinic staff (scientists, clinicians, administrators, etc.) creating new insights, conducting research, and/or developing new AI models with Mayo Clinic Platform’s (MCP) de-identified clinical data and data science tools. Mayo Clinic Platform is a federated, privacy-preserving infrastructure that enables partners to contribute and access diverse clinical data for research, AI training, and discovery at unprecedented scale. 

The Sr. Data Science Analyst will establish and execute on all data-related aspects of the Mayo Clinic Platform’s Shields Enablement Program. The Shields Enablement program is how we bring platform thinking, data, and tools to the diverse staff of Mayo Clinic.   

The position will be responsible for the following essential functions:  

• Serve as the primary point of contact for all data-related questions from Mayo Clinic users. Address and triage data questions as they arise and facilitate coordination with data science support teams.  
• Work directly with MCP’s clinical data and data science support team to make requisite real-world clinical data and tools available for Mayo Clinic data science workspaces.  
• Plan and scope analytical projects, clean and prepare datasets, perform statistical analyses, and develop and test models for clinical research and deployment projects with Mayo Clinic staff. 
• Work with Platform services, data, and Shields Enablement staff to onboard new users and execute discovery projects.  
• Serve as a liaison to technical-related internal and external partnerships to co-develop models, collaborative research, and new discovery of insights 
• Assist with the creation and collection of metrics to ensure the success of the Shields Enablement Program.  

The above statements describe the general nature and level of work only. They are not an exhaustive list of all required responsibilities, duties, and skills. Other duties may be added or assigned.