Senior Data Science Analyst

Mayo Clinic•Rochester, MN

2d•Hybrid

About The Position

This hybrid position requires the employee to be located within 100 miles of Mayo Clinic’s Rochester, Minnesota campus. Data scientists at Mayo Clinic analyze large, heterogeneous datasets to discover patterns and insights that can improve patient health and augment human capabilities. The role applies advanced artificial intelligence, machine learning, statistical processing, and other data science methods to healthcare and business challenges. It may involve working with knowledge architects, informaticians, clinicians, and external partners to develop and deploy analytics and AI applications for nontechnical users, including at the point of care. The analyst provides advanced data insights for complex business problems using structured and unstructured data. The role may involve modifying scripts or software applications for data management, extraction, analysis, and AI; developing predictive and prescriptive models on large-scale datasets; offering enterprise-level consultative services; and supporting scientific projects under the supervision of a designated senior-level data scientist. The analyst participates in stakeholder discovery, identifies business requirements and expected outcomes, and leads the interpretation of analyses and preparation of reports. This position is not eligible for visa sponsorship or transfer, and Mayo Clinic does not participate in the F-1 STEM OPT extension program. The selection process may include an OnDemand, prerecorded interview. Applicants must submit a CV or resume and unofficial or official college transcripts. Applicants with foreign education must provide, at their own expense, a detailed equivalency evaluation showing the U.S.-equivalent degree from an organization listed with NACES or AICE.

Requirements

Bachelor’s degree in a relevant field such as engineering, mathematics, computer science, or health science, plus at least 12 graduate-level semester hours in domain-relevant sciences; alternatively, seven or more years of data science and AI experience.
Advanced expertise in AI, machine learning, deep learning, statistical data processing, regression, neural networks, decision trees, clustering, pattern recognition, probability theory, data science methods, and the mathematical theories underlying these tools.
Advanced 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.
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.
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 problem-solving methodologies, planning techniques, continuous improvement methods, project management methods, and analytical tools and methodologies such as machine learning, statistical packages, and modeling.
Ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes.
Strong time-management skills, analytical skills, 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.
Submit a CV or resume and unofficial or official college transcripts. Applicants with foreign education must provide a detailed U.S. degree equivalency evaluation from a NACES- or AICE-listed organization, at their own expense.

Nice To Haves

PhD or Master’s degree with one year of experience in a relevant field such as engineering, mathematics, computer science, health science, or another analytical or quantitative field, and at least one year of professional or research experience in data.
Demonstrated ability to provide consultative services to departments, divisions, and committees from Mayo entities requesting assistance.

Responsibilities

Analyze large, heterogeneous datasets to discover patterns and insights related to patient health and business needs.
Provide advanced data insights for complex business problems using structured and unstructured data.
Work with staff and, as needed, knowledge architects, informaticians, clinicians, and external partners to develop data-analysis tools, predictive models, and AI/ML solutions.
Modify existing scripts or software applications to support data management, extraction, analysis, and AI.
Develop predictive and prescriptive models on large-scale datasets using advanced statistical modeling, operations research, machine learning, or data mining techniques.
Participate in stakeholder discovery to identify business requirements and expected outcomes.
Lead the interpretation of data analysis and the writing of reports.
May provide enterprise-level consultative services to departments, divisions, and committees, or support scientific projects under the supervision of a designated senior-level data scientist.
May help develop and deploy analytics and AI applications for nontechnical users, including at the point of care.
Manage varied project workloads and priorities, and stay current on healthcare trends and enterprise changes.