Principal Data Science Analyst (supplemental )-Dispenzieri

Data Scientists at Mayo Clinic perform detailed analysis of large bodies of heterogeneous data in order to discover new patterns and insights having an impact upon patient health and augmenting human capabilities. Candidate has deep expertise in AI, machine learning, deep learning, statistical data processing, regression techniques, neural networks, decision trees, clustering, pattern recognition, probability theory and data science methods and the mathematical theories underlying these tools used to analyze data. Has deep knowledge of healthcare data types, topics, and scientific challenges and approaches.
Work with knowledge architects, informaticians and clinicians at Mayo, and partner outside companies to develop and deploy applications to bring AI and analytic solutions to nontechnical users, often at the point of care.. Designs and develops scripts or software applications to support data management, data extraction, data analysis, and AI as required. This position may develop predictive and prescriptive models to address complex problems, discover insights, and identify opportunities using machine learning, statistical techniques, and data mining. Provides Consultative Services at an enterprise level to departments/divisions and/or may lead scientific projects. May have direct and indirect reports.

Other responsibilities:
•Provides deep data insights for complex business problems that can be approached with analytics techniques to collect, explore, and extract insights from structured and unstructured data.
•Develops predictive and prescriptive models to address complex problems, discover insights, and identify opportunities using machine learning, statistical techniques, and data mining.
•Makes presentations on assigned projects or proposals.
•Conducts advanced data analysis and designs highly complex algorithm systems.
•Functions independently and initiates judgment in handling delegated responsibilities.
•Experience leading technical/quantitative teams.
•Develops experimental design approaches to validate findings or test hypotheses.
•Identifies/creates the appropriate algorithm to discover patterns.
•Leads and directs the interpretation of data analysis and writing reports.

Qualifications

A Master's degree in a relevant field such as engineering, mathematics, computer science, health science, or other analytical/quantitative and a minimum of five years of professional or research experience in data science
The preferred candidate will possess a PhD in a relevant field such as engineering, mathematics, computer science, health science, or other analytical/quantitative field and a minimum of three years of professional or research experience in data science and statistical/machine learning packages.

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. Deep 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 at an institutional or enterprise level 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 independently manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes. Excellent interpersonal skills to include presentation, negotiation, persuasion, and written communications skills are required. Exceptional time management is required. In addition, requires excellent 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.

Why Mayo Clinic

Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans – to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic.

Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is.

Equal Opportunity

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the "EOE is the Law". Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization.