Senior Data Science Analyst - AI Program

** Why Mayo Clinic*
* Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans ((Use the "Apply for this Job" box below).)  - to take care of you and your family, now and in the future.

And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic.

** Benefits Highlights*
* + Medical:
Multiple plan options.

+ Dental:
Delta Dental or reimbursement account for flexible coverage.

+ Vision:
Affordable plan with national network.

+ Pre-Tax Savings: HSA and FSAs for eligible expenses.

+ Retirement:
Competitive retirement package to secure your future.

** Responsibilities*
* Data Scientists at Mayo Clinic perform detailed analysis of large bodies of heterogeneous healthcare data, including imaging, genomics, clinical text, structured EHR data, signals, and other healthcare modalities to discover new patterns and insights having an impact upon patient health and augmenting human capabilities. Candidate has deep expertise in AI, machine learning, deep learning, multimodal model development, 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 used to analyze data.

Has deep knowledge of healthcare data types, modalities, topics, and scientific challenges, including how large language models and multimodal foundation models are built, adapted, evaluated, and safely applied in healthcare settings.

May work with knowledge architects, informaticians and clinicians at Mayo, and partner outside companies to develop and deploy applications to bring AI, foundation model and analytic solutions to nontechnical users, often at the point of care. Applies and modifies existing scripts or software applications to support data management, data extraction, data analysis, and AI as required

May develop predictive models on large-scale datasets to address various business problems through leveraging advanced statistical modeling, operations research, machine learning, or data mining techniques. May provide Consultative Services at an enterprise level to departments/divisions and/or support scientific projects under the supervision of a designated senior level data scientist.

Other responsibilities:

+ Applies analytics techniques to extract insights from structured, unstructured, and multimodal healthcare data, including text, imaging, genomics, and other clinical data types.

+ Develops predictive, prescriptive, generative, and multimodal models to address complex healthcare problems, discover insights, and identify opportunities using machine learning, statistical techniques, data mining, and foundation model approaches.

+ Will work with other staff in developing data analysis tools and predictive models, using advanced data analysis techniques and artificial intelligence and machine learning.

+ Participates in discovery processes with stakeholders to identify the business requirements and the expected outcome.

+ Supports the use and adaptation of algorithms and models, including machine learning, LLM, and multimodal approaches, to identify patterns across healthcare data modalities.

+ Applies working knowledge of LLMs and foundation models to support prompting, evaluation, and safe use in healthcare applications.

+ Leads the interpretation of data analysis and writing reports.

** Qualifications*
* A Bachelor's degree in a relevant field such as engineering, mathematics, computer science, health science and at least 12 graduate level semester hours in domain-relevant sciences or seven years or more of data science and AI experience.

The preferred candidate will possess a PhD or Master's degree with one year experience in a relevant field such as engineering, mathematics, computer science, health science, or other analytical/quantitative field and a minimum of one year of professional or research experience in data.

The successful candidate will need to have both technical and business background/experience along with strong leadership skills. Good written and oral communication skills are required. Expertise in the use of scientific computing and data management packages. Ability to prioritize, organize, and delegate…