We are seeking a highly skilled and innovative sr. data analyst to join our dynamic department, focusing on the design and development of intuitive and user-friendly interfaces for our AI and data analysis projects in the healthcare sector. This role requires a unique blend of creativity, technical proficiency, and a deep understanding of user experience principles to deliver effective web, mobile, and desktop applications that meet the complex needs of healthcare professionals and patients.
The responsibility of this position is the development of proof-of-concept pilot demonstrations to validate the practicality and effectiveness of AI tools in real-world healthcare settings. AI technologies sometimes remain confined within research environments due to the complexity of their integration into existing clinical workflows. A User Interface Developer specializes in creating intuitive, user-friendly interfaces that can make sophisticated AI tools accessible to healthcare professionals without requiring them to have in-depth technical knowledge. This accessibility is crucial for the adoption of AI technologies in everyday clinical practice, as it ensures that the benefits of AI can be leveraged to improve patient outcomes and operational efficiency. Through close collaboration with IT and other departments, the User Interface Developer helps navigate the complex healthcare environment, ensuring that AI tools are designed with both current needs and future deployments in mind.
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.
During the selection process you may participate in an OnDemand (pre-recorded) interview that you can complete at your convenience. During the OnDemand interview, a question will appear on your screen, and you will have time to consider each question before responding. You will have the opportunity to re-record your answer to each question – Mayo Clinic will only see the final recording. The complete interview will be reviewed by a Mayo Clinic staff member and you will be notified of next steps.
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