Principal Data Science Analyst - Pioneering Science

Mayo Clinic•Rochester, MN

65d•$145,454 - $218,234

About The Position

Mayo Clinic is a top-ranked healthcare provider dedicated to patient needs and employee well-being, offering competitive compensation, comprehensive benefits, and opportunities for career advancement. Data Scientists at Mayo Clinic analyze large, diverse datasets to uncover patterns and insights that impact patient health and enhance human capabilities. This role requires deep expertise in AI, machine learning, deep learning, statistical processing, and various data science methodologies, along with a strong understanding of healthcare data and challenges. The position involves collaborating with internal and external partners to develop and deploy AI and analytic solutions for non-technical users, often at the point of care. Responsibilities include designing and developing scripts and software for data management, extraction, and analysis, as well as creating predictive and prescriptive models. The role also entails providing enterprise-level consultative services and potentially leading scientific projects.

Requirements

Master’s degree in a relevant field such as engineering, mathematics, computer science, health science, or other analytical/quantitative field.
A minimum of 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 and data science methods and the mathematical theories underlying these tools.
Deep knowledge of healthcare data types, topics, and scientific challenges and approaches.
Technical and business background/experience.
Strong leadership skills.
Good written and oral communication skills.
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.
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 and stay current on healthcare trends and enterprise changes.
Excellent interpersonal skills to include presentation, negotiation, persuasion, and written communications skills.
Exceptional time management.
Excellent analytical skills.
Consulting skills.
Ability to identify and recommend solutions.
Advanced computer application skills.
Commitment to customer service.
Experience with data modeling and data exploration tools.
Must be a U.S. citizen, permanent resident, refugee or asylee.

Nice To Haves

PhD in a relevant field such as engineering, mathematics, computer science, health science, or other analytical/quantitative field.
A minimum of three years of professional or research experience in data science and statistical/machine learning packages.
Demonstrated ability to provide consultative services at an institutional or enterprise level to departments/divisions and committees from any Mayo entity requesting assistance.
Advanced SQL and production-level Python experience.
Experience with cloud platforms, such as Google Cloud Platform.
Experience developing analytic applications, APIs, or internal tools using sound software engineering practices.
Experience building reproducible data pipelines with recurring runs, environment management, audit trails, and evolving data.
Direct experience with EHR or clinical research data, including common models, standards, and vocabularies such as Epic Clarity/Caboodle, OMOP, FHIR, ICD-10, CPT, LOINC, RxNorm, or SNOMED.
Knowledge of cohort identification, observational study design, survival analysis, clinical prediction modeling, and common sources of bias in real-world data.
Practical experience applying NLP or LLMs to clinical or research workflows, including evaluation, validation, and appropriate use of simpler alternatives when warranted.
Ability to partner with clinicians and researchers, translate clinical questions into analytic plans, and communicate findings clearly.

Responsibilities

Perform detailed analysis of large bodies of heterogeneous data to discover new patterns and insights impacting patient health and augmenting human capabilities.
Work with knowledge architects, informaticians, and clinicians to develop and deploy applications that bring AI and analytic solutions to non-technical users.
Design and develop scripts or software applications to support data management, data extraction, data analysis, and AI.
Develop predictive and prescriptive models to address complex problems, discover insights, and identify opportunities using machine learning, statistical techniques, and data mining.
Provide consultative services at an enterprise level to departments/divisions and may lead scientific projects.
Provide 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.
Make presentations on assigned projects or proposals.
Conduct advanced data analysis and design highly complex algorithm systems.
Function independently and exercise judgment in handling delegated responsibilities.
Develop experimental design approaches to validate findings or test hypotheses.
Identify/create the appropriate algorithm to discover patterns.
Lead and direct the interpretation of data analysis and writing reports.