We are seeking a talented and motivated Healthcare AI and Data Analyst to join our department, focusing on the development and application of Natural Language Processing (NLP), Large Language Models (LLM), and deep learning techniques to address various clinical challenges. This role is pivotal in advancing our healthcare organization's capabilities in AI-driven research and clinical applications. The ideal candidate will have a strong background in AI, machine learning, and data analytics, with a passion for transforming healthcare through technology. Key responsibilities include to design, develop, and implement NLP, LLM, and deep learning models to support different clinical applications. This includes data preprocessing, model training, and validation. The data analyst will assist faculty and research teams in conducting preliminary studies and experiments to establish new collaborations across disciplines. This position will also support the preparation of manuscripts for publication in peer-reviewed journals. This involves data analysis, visualization, interpretation of results, and drafting of the methodology and results sections related to AI and data analytics.

Data Scientists at Mayo Clinic perform detailed analysis of large bodies of heterogeneous data in order to discover new patterns and insights having an impact upon patient health and augmenting human capabilities. Candidate has advanced expertise in AI, machine learning, deep learning, 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 advanced knowledge of healthcare data types, topics, and scientific challenges and approaches.

May work with knowledge architects, informaticians and clinicians at Mayo, and partner outside companies to develop and deploy applications to bring AI 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:
•Provides advanced data insights for complex business problems that can be approached with analytics techniques to collect, explore, and extract insights from structured and unstructured data.
•Has advanced expertise in the methods used to analyze data and advanced knowledge of data types, topics, and scientific challenges and 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.
•Leads the interpretation of data analysis and writing reports.

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 preferred candidate will have: 

- Demonstrated experience in developing NLP, LLM, and deep learning models, preferably in a healthcare or clinical research setting.

- Proficiency in programming languages and tools commonly used in AI and data analysis, such as Python, R, TensorFlow, PyTorch, and relevant NLP libraries.

- Strong analytical skills, with the ability to manage and analyze large datasets, and interpret complex data to derive meaningful insights.

- Experience in scientific writing and manuscript preparation, with a track record of contributing to published research or technical reports.

- Excellent communication and collaboration skills, with the ability to work effectively in multidisciplinary teams and support non-technical stakeholders.

- Knowledge of healthcare data privacy regulations and ethical guidelines for AI applications in clinical settings.

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 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 various tasks on projects. Demonstrated initiative in administration, education (seminars, training), software development, and technical reports. Demonstrated success in project management and communication skills. Demonstrated ability to develop predictive and prescriptive models on large-scale datasets to address various business problems through leveraging advanced statistical modeling, machine learning, or data mining techniques. Demonstrated ability to provide consultative services to departments/divisions and committees from any Mayo entity requesting assistance is preferred. Demonstrated application of several problem-solving methodologies, planning techniques, continuous improvement methods, project management methods, and analytical tools and methodologies (e.g. machine learning, statistical packages, modeling, etc.) required. Incumbent must have ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes. Strong interpersonal skills to include presentation, negotiation, persuasion, and written communications skills are required. Strong time management skills also are required. In addition, requires strong analytical skills, consulting skills, ability to identify and recommend solutions, advanced computer application skills and a commitment to customer service. Experience with data modeling and date exploration tools.