Clinical Data Analyst Internship Jobs in Rochester, MN

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.

• Advance AI and machine learning solutions specifically for digital pathology and multimodal clinical data.
• Work as part of an AI Operations team focused on moving AI models into clinically deployable products in collaboration with clinical, technical, enterprise informatics, IT, and regulatory teams.
• Support the full AI product development lifecycle by establishing best practices for model evaluation, quality assurance, reproducibility, and regulatory documentation.
• Collaborate directly with pathologists, laboratory physicians, clinicians, computational scientists, enterprise informatics, IT, regulatory teams, and software engineering teams.
• Develop AI solutions that address real-world clinical needs, not only general business or scientific problems.
• Emphasize clinical translation of AI/ML solutions, moving beyond data analysis and predictive modeling into operational clinical use.

We require a two year commitment to this position

**This position is not eligible for visa sponsorship. Also, Mayo Clinic DOES NOT participate in the F-1 STEM OPT extension program**

  A master's degree in engineering, computer science, mathematics, health science, or a related field with 4 years of experience, a bachelor's degree with 6 years of experience. 
  Extensive experience applying AI and machine learning in production healthcare environments or similar highly regulated or technology focused industries, showcasing an understanding of healthcare technology.
  Demonstrated leadership in managing complex projects, with a proven ability to navigate intricate project requirements and deliver successful outcomes.
  Proficiency in fostering collaboration across diverse teams and effectively communicating complex technical concepts to non-technical stakeholders.
  Demonstrated expertise in cloud infrastructure environment and software development tools.
  Experience working with large, complex, and heterogeneous data sets, preferably in healthcare. 
  Skilled in AI/ML techniques and frameworks.
  Familiarity with best practices in data engineering, data science, AI Engineering, and the MLOps communities.
  Demonstrated initiative in administration, education, software development, and technical reporting. 
  A commitment to mentoring and training less-experienced team members, coupled with strong interpersonal, communication, and time management skills.

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Additional preferred/desired qualifications/experience:

• Experience developing, validating, or deploying AI/ML models in healthcare, pathology, laboratory medicine, or clinical operations.
• Familiarity with multimodal clinical data, digital pathology images, whole-slide imaging, image analysis, including integration of imaging, laboratory, pathology, molecular, structured EHR, and unstructured clinical data.
• Experience with MLOps, model lifecycle management, model monitoring, version control, reproducible pipelines, or scalable deployment workflows.
• Experience translating AI/ML models from proof-of-concept into operational, production-ready, or clinically deployable solutions.
• Working knowledge of cloud-based or enterprise-scale data science environments, high-performance computing, or secure healthcare data platforms.
• Proficiency with Python, R, SQL, machine learning frameworks, statistical modeling tools, and data visualization methods.
• Strong ability to communicate complex technical concepts to nontechnical clinical, operational, and executive audiences.

  A master's degree in engineering, computer science, mathematics, health science, or a related field with 4 years of experience, a bachelor's degree with 6 years of experience. 
  Extensive experience applying AI and machine learning in production healthcare environments or similar highly regulated or technology focused industries, showcasing an understanding of healthcare technology.
  Demonstrated leadership in managing complex projects, with a proven ability to navigate intricate project requirements and deliver successful outcomes.
  Proficiency in fostering collaboration across diverse teams and effectively communicating complex technical concepts to non-technical stakeholders.
  Demonstrated expertise in cloud infrastructure environment and software development tools.
  Experience working with large, complex, and heterogeneous data sets, preferably in healthcare. 
  Skilled in AI/ML techniques and frameworks.
  Familiarity with best practices in data engineering, data science, AI Engineering, and the MLOps communities.
  Demonstrated initiative in administration, education, software development, and technical reporting. 
  A commitment to mentoring and training less-experienced team members, coupled with strong interpersonal, communication, and time management skills.

.

Additional preferred/desired qualifications/experience:

• Experience developing, validating, or deploying AI/ML models in healthcare, pathology, laboratory medicine, or clinical operations.
• Familiarity with multimodal clinical data, digital pathology images, whole-slide imaging, image analysis, including integration of imaging, laboratory, pathology, molecular, structured EHR, and unstructured clinical data.
• Experience with MLOps, model lifecycle management, model monitoring, version control, reproducible pipelines, or scalable deployment workflows.
• Experience translating AI/ML models from proof-of-concept into operational, production-ready, or clinically deployable solutions.
• Working knowledge of cloud-based or enterprise-scale data science environments, high-performance computing, or secure healthcare data platforms.
• Proficiency with Python, R, SQL, machine learning frameworks, statistical modeling tools, and data visualization methods.
• Strong ability to communicate complex technical concepts to nontechnical clinical, operational, and executive audiences.