Data Scientist - AI Program

Mayo ClinicRochester, MN

About The Position

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. This position works in conjunction with Data Science and Informatics faculty to provide technical thought leadership on data science at Mayo. Candidate has extensive expertise in navigating the whole spectrum of transforming data to information to knowledge and to wisdom including problem formulation, data acquisition, modeling, learning strategy, and interpretation with extensive hands-on experience. Provide strategic direction regarding data science and AI in a specific area (e.g., cancer, surgery, planning services, marketing, healthcare delivery). Work with enterprise leaderships to advance digital strategy at Mayo Clinic. Works closely with Informatics and IT teams to create data and intelligence driven systems to solve complex client problems. Makes strategic recommendations on data collection, integration and retention requirements, incorporating business requirements and knowledge of best practices. Supports scientific projects under the loose supervision of a designated senior level data scientist, or under self-direction. Designs, develops, applies and modifies scripts or software applications to support data management, data extraction and data analysis as required. Provides Consultative Services at an enterprise level to departments/divisions. Is responsible to gather, analyze, present findings to leadership. Other responsibilities: Participates in multidisciplinary teams to design, develop, and recommend new approaches for data driven decision-making. Leads discovery processes on pioneering AI/ML based approaches to solve complex data problems across a variety of domains. Has deep expertise in the methods used to analyze data and deep knowledge of data types, topics, and scientific challenges and approaches that will be used to help inform and define new products, experiences and technologies. Guides and educates the data science team to provide unbiased and accurate information, analysis, consultation, and recommendations to support strategic and operational data science initiatives at Mayo Clinic. Will develop analytics tools that can be used by other staff with non-technical expertise.

Requirements

  • PhD degree in domain-relevant sciences (mathematics, computer science, statistics, physics, data science, engineering, health science or other domain-relevant field).
  • At least four years of informatics, Artificial Intelligence, data science and/or machine learning experience.
  • Both technical and business background/experience.
  • Strong leadership skills.
  • Experience leading technical/quantitative teams.
  • In-depth business or practice knowledge.
  • Demonstrated ability to develop predictive and prescriptive models on large-scale datasets using advanced statistical modeling, machine learning, or data mining techniques.
  • 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.).
  • Ability to independently manage a varied workload of projects with multiple priorities.
  • Ability to stay current on healthcare trends and enterprise changes.
  • Excellent interpersonal skills including presentation, negotiation, persuasion, and written communications skills.
  • Exceptional time management skills.
  • Excellent analytical skills.
  • Consulting skills.
  • Ability to deploy data science solutions.
  • Ability to identify and recommend solutions.
  • Advanced computer application skills.
  • Commitment to customer service.
  • Experience with data modeling and data exploration tools.
  • Expertise in the use of scientific computing and data management packages.
  • Demonstrated ability to prioritize, organize, and delegate various tasks on projects.
  • Demonstrated initiative in administration, education (seminars, training), software development, and technical reports.
  • Demonstrated ability to provide vision and strategic direction at an institutional or enterprise level to departments/divisions and committees.

Responsibilities

  • Perform detailed analysis of large bodies of heterogeneous data to discover new patterns and insights impacting patient health and augmenting human capabilities.
  • Provide technical thought leadership on data science at Mayo in conjunction with Data Science and Informatics faculty.
  • Navigate the transformation of data to information, knowledge, and wisdom, including problem formulation, data acquisition, modeling, learning strategy, and interpretation.
  • Provide strategic direction regarding data science and AI in specific areas (e.g., cancer, surgery, planning services, marketing, healthcare delivery).
  • Advance digital strategy at Mayo Clinic by working with enterprise leadership.
  • Create data and intelligence driven systems to solve complex client problems in collaboration with Informatics and IT teams.
  • Make strategic recommendations on data collection, integration, and retention requirements, incorporating business requirements and best practices.
  • Support scientific projects under loose supervision or self-direction.
  • Design, develop, apply, and modify scripts or software applications for data management, extraction, and analysis.
  • Provide enterprise-level consultative services to departments/divisions.
  • Gather, analyze, and present findings to leadership.
  • Participate in multidisciplinary teams to design, develop, and recommend new approaches for data-driven decision-making.
  • Lead discovery processes on pioneering AI/ML based approaches to solve complex data problems across various domains.
  • Guide and educate the data science team to provide unbiased and accurate information, analysis, consultation, and recommendations for strategic and operational data science initiatives.
  • Develop analytics tools for staff with non-technical expertise.
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