Join a world class team that’s transforming the future of healthcare. At Mayo Clinic, Senior Data Science Analysts play a pivotal role in advancing patient care through data driven discovery, cutting edge AI solutions, and meaningful clinical impact. If you’re passionate about solving complex problems and creating technologies that directly improve lives, this is the place for you.

What You’ll Do

As a Mayo Clinic Senior Data Science Analyst, you will:

•    Unlock insights from large, complex, heterogeneous datasets to support clinical decision making and enhance human capabilities
•    Apply advanced expertise in AI, machine learning, and deep learning, including regression modeling, neural networks, clustering, pattern recognition, decision trees, and statistical data processing
•    Work hands on with rich healthcare datasets, leveraging deep knowledge of medical data types, scientific challenges, and analytic approaches
•    Collaborate with multidisciplinary teams—including knowledge architects, informaticians, clinicians, and external industry partners—to design and deploy AI driven tools for real world use, often at the point of care
•    Develop predictive models and analytics solutions that address high impact operational, clinical, and research problems
•    Build and enhance data pipelines, scripts, and applications that support data extraction, management, analysis, and AI deployment
•    Provide consultative expertise across departments and scientific project teams, with guidance from senior data scientists
•    Lead the interpretation and communication of analytical results, transforming data insights into actionable recommendations

Key Responsibilities

•    Deliver advanced analytics solutions that uncover insights from both structured and unstructured data
•    Drive the development of analytical tools and predictive models using AI/ML techniques
•    Partner with stakeholders to understand business needs and design solutions aligned with expected outcomes
•    Communicate findings through clear, compelling reports that support decision making and strategic planning

•    Bachelor’s degree in engineering, mathematics, computer science, health science, or a related analytical field

•    Plus one of the following:

o    At least 12 graduate level semester hours in domain relevant sciences, or
o    Seven or more years of hands-on experience in data science, AI, or related analytical disciplines

Preferred Qualifications

•    Master’s degree or PhD in engineering, mathematics, computer science, health science, or another quantitative field
•    At least one year of professional or research experience working with data, analytics, or machine learning

What Makes a Strong Candidate

•    A blend of technical depth and business acumen, with the ability to translate complex data findings into actionable insights
•    Proven leadership skills, with experience guiding projects, mentoring team members, or influencing decision makers
•    Excellent communication skills, both written and verbal—capable of telling a compelling story with data
•    Advanced proficiency with scientific computing tools, data management packages, and modern analytics technologies
•    Strong project management abilities, including prioritizing multiple tasks, delegating effectively, and delivering results on time
•    Demonstrated initiative in areas such as education/training, software development, report writing, or data driven process improvement
•    Experience developing predictive and prescriptive models on large scale datasets using ML, statistical modeling, or data mining techniques
•    Ability to provide consultative analytics support across diverse departments and teams
•    Skilled in applying problem solving frameworks, continuous improvement methods, and analytical methodologies
•    Strong interpersonal strengths, including presentation, negotiation, collaboration, and stakeholder engagement
•    Excellent time management and the ability to adapt to shifting priorities in a fast-paced environment
•    Commitment to customer service, with the ability to recommend solutions, support non-technical users, and deliver high quality analytical outcomes
•    Experience with data modeling, exploratory data analysis, and modern data exploration tools