Principal Data Science Analyst

** 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.

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.. Designs and develops scripts or software applications to support data management, data extraction, data analysis, and AI as required. This position may develop predictive and prescriptive models to address complex problems, discover insights, and identify opportunities using machine learning, statistical techniques, and data mining.

Provides Consultative Services at an enterprise level to departments/divisions and/or may lead scientific projects.

May have direct and indirect reports.

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.

+ Makes presentations on assigned projects or proposals.

+ Conducts advanced data analysis and designs highly complex algorithm systems.

+ Functions independently and initiates judgment in handling delegated responsibilities.

+ Experience leading technical/quantitative teams.

+ Develops experimental design approaches to validate findings or test hypotheses.

+ Identifies, creates, or adapts appropriate algorithms and models, including LLMs and multimodal foundation models, to discover patterns across healthcare data modalities.

+ Applies knowledge of how LLMs and foundation models are trained, fine-tuned, prompted, evaluated, and governed to support safe and effective use in healthcare applications.

+ Leads and directs the interpretation of data analysis and writing reports.

** Qualifications*
* A Master's degree in a relevant field such as engineering, mathematics, computer science, health science, or other analytical/quantitative and a minimum of five years of professional or research experience in data science

The preferred candidate will possess a PhD in a relevant field such as engineering, mathematics, computer science, health science, or other analytical/quantitative field and a minimum of three years of professional or research experience in data science and statistical/machine learning packages.

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. Deep expertise in the use of scientific computing and data…