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.  

A Bachelor’s degree in a relevant field such as engineering, mathematics, computer science, health science and at least 12 graduate level semester hours in domain-relevant sciences or seven years or more of data science and AI experience.
The preferred candidate will possess a PhD or Master’s degree with one year experience in a relevant field such as engineering, mathematics, computer science, health science, or other analytical/quantitative field and a minimum of one year of professional or research experience in data.

The successful candidate will need to have both technical and business background/experience along with strong leadership skills. Good written and oral communication skills are required. Expertise in the use of scientific computing and data management packages. Ability to prioritize, organize, and delegate various tasks on projects. Demonstrated initiative in administration, education (seminars, training), software development, and technical reports. Demonstrated success in project management and communication skills. Demonstrated ability to develop predictive and prescriptive models on large-scale datasets to address various business problems through leveraging advanced statistical modeling, machine learning, or data mining techniques. Demonstrated ability to provide consultative services to departments/divisions and committees from any Mayo entity requesting assistance is preferred. Demonstrated application of several problem-solving methodologies, planning techniques, continuous improvement methods, project management methods, and analytical tools and methodologies (e.g. machine learning, statistical packages, modeling, etc.) required. Incumbent must have ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes. Strong interpersonal skills to include presentation, negotiation, persuasion, and written communications skills are required. Strong time management skills also are required. In addition, requires strong analytical skills, consulting skills, ability to identify and recommend solutions, advanced computer application skills and a commitment to customer service. Experience with data modeling and date exploration tools.