Senior Data Science Analyst - AI Program

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.