Principal Data Science Analyst (supplemental )-Dispenzieri

Mayo Clinic•Rochester, MN

1d•$70 - $105

About The Position

Data Scientists at Mayo Clinic analyze large, heterogeneous datasets to discover patterns and insights that can improve patient health and augment human capabilities. This role requires deep expertise in artificial intelligence, machine learning, deep learning, statistical data processing, regression, neural networks, decision trees, clustering, pattern recognition, probability theory, data science methods, and the mathematical foundations of these techniques, as well as knowledge of healthcare data and scientific challenges. The analyst works with Mayo Clinic knowledge architects, informaticians, and clinicians, as well as external partners, to develop and deploy AI and analytics applications for nontechnical users, including at the point of care. The position designs and develops scripts or software applications for data management, extraction, analysis, and AI. It may develop predictive and prescriptive models to solve complex problems, discover insights, and identify opportunities. The role provides enterprise-level consulting services to departments and divisions and may lead scientific projects. It may have direct and indirect reports. The successful candidate brings technical and business experience, leadership, strong communication, and project-management skills. The role independently manages a varied workload, prioritizes and delegates project tasks, stays current with healthcare trends and enterprise changes, and applies analytical and continuous-improvement methodologies. Mayo Clinic offers competitive compensation, comprehensive benefits, continuing education, and advancement opportunities.

Requirements

Master's degree in a relevant field such as engineering, mathematics, computer science, health science, or another analytical or quantitative field.
At least five years of professional or research experience in data science.
Deep expertise in AI, machine learning, deep learning, statistical data processing, regression techniques, neural networks, decision trees, clustering, pattern recognition, probability theory, data science methods, and their mathematical foundations.
Knowledge of healthcare data types, topics, scientific challenges, and approaches.
Technical and business background or experience, with strong leadership skills.
Strong written and oral communication skills, including presentation, negotiation, persuasion, and written communications.
Deep expertise in scientific computing and data management packages.
Ability to prioritize, organize, and delegate project tasks.
Demonstrated initiative in administration, education such as seminars and training, software development, and technical reports.
Demonstrated success in project management and communication.
Ability to develop predictive and prescriptive models on large-scale datasets using advanced statistical modeling, machine learning, or data mining.
Demonstrated application of problem-solving methodologies, planning techniques, continuous-improvement methods, project-management methods, and analytical tools and methodologies.
Ability to independently manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes.
Excellent analytical and consulting skills, ability to identify and recommend solutions, advanced computer application skills, and commitment to customer service.
Experience with data modeling and data exploration tools.
Exceptional time-management skills.

Nice To Haves

PhD in a relevant field such as engineering, mathematics, computer science, health science, or another analytical or quantitative field, with at least three years of professional or research experience in data science and statistical or machine-learning packages.
Demonstrated ability to provide consultative services at an institutional or enterprise level to departments, divisions, and committees across Mayo entities.

Responsibilities

Provide deep data insights for complex business problems by collecting, exploring, and extracting insights from structured and unstructured data.
Develop predictive and prescriptive models using machine learning, statistical techniques, and data mining.
Present assigned projects and proposals.
Conduct advanced data analysis and design highly complex algorithm systems.
Handle delegated responsibilities independently and exercise judgment.
Lead technical or quantitative teams.
Develop experimental designs to validate findings or test hypotheses.
Identify or create appropriate algorithms to discover patterns.
Lead and direct interpretation of data analyses and report writing.
Work with knowledge architects, informaticians, clinicians, and external partners to develop and deploy AI and analytics applications, including applications used by nontechnical users at the point of care.
Design and develop scripts or software applications for data management, data extraction, data analysis, and AI.
Provide enterprise-level consultative services to departments, divisions, and committees, and potentially lead scientific projects.
Prioritize, organize, and delegate project tasks; independently manage multiple projects and priorities.
Apply problem-solving methodologies, planning techniques, continuous-improvement methods, project-management methods, and analytical tools and methodologies.