Principal Data Science Analyst (supplemental )-Dispenzieri

Mayo Clinic•Rochester, MN

1d•$70 - $105

About The Position

Mayo Clinic’s Principal Data Science Analyst performs detailed analysis of large, heterogeneous datasets to identify patterns and insights that can improve patient health and augment human capabilities. The role applies advanced AI, machine learning, deep learning, statistical data processing, and other data science methods, supported by knowledge of healthcare data and scientific challenges. The analyst works with knowledge architects, informaticians, clinicians, and external partner companies to develop and deploy AI and analytics applications for nontechnical users, often at the point of care. The role also designs and develops scripts or software to support data management, extraction, analysis, and AI, and may develop predictive and prescriptive models for complex problems. This position provides enterprise-level consultation to departments and divisions and may lead scientific projects and technical or quantitative teams. It independently handles delegated responsibilities, manages varied project workloads, and leads interpretation of analyses and reporting. The posting notes that the role may have direct and indirect reports.

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 underlying mathematical theories.
Deep knowledge of healthcare data types, topics, scientific challenges, and approaches.
Technical and business background or experience, along 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 or 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 techniques.
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.
Exceptional time management.
Experience with data modeling and data exploration tools.

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, or committees across Mayo entities.

Responsibilities

Analyze large bodies of heterogeneous data to discover patterns and insights relevant to patient health and human capabilities.
Work with Mayo Clinic knowledge architects, informaticians, clinicians, and external companies to develop and deploy AI and analytics applications for nontechnical users, often at the point of care.
Design and develop scripts or software applications that support data management, data extraction, data analysis, and AI.
Develop predictive and prescriptive models using machine learning, statistical techniques, and data mining.
Provide deep data insights for complex business problems by collecting, exploring, and extracting insights from structured and unstructured data.
Present assigned projects or proposals.
Conduct advanced data analysis and design highly complex algorithm systems.
Function independently and exercise judgment in handling delegated responsibilities.
Lead technical or quantitative teams and, as applicable, direct and indirect reports.
Develop experimental design approaches to validate findings or test hypotheses.
Identify or create appropriate algorithms to discover patterns.
Lead and direct interpretation of data analyses and the writing of reports.
Provide consultative services at an enterprise level to departments or divisions and/or lead scientific projects.
Manage varied project workloads with multiple priorities and stay current on healthcare trends and enterprise changes.