Data Science Analyst - Gastroenterology Research

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 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 used to analyze data.
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 datasets to address various business problems by leveraging statistical modeling, operations research, machine learning, or data mining techniques. May provide Consultative Services to departments/divisions and/or support scientific projects under the guidance of a designated senior level data scientist.

Other responsibilities:
•Provides data insights for business problems that can be approached with analytics techniques to collect, explore, and extract insights from structured and unstructured data.
•Has expertise in the data science methods used to analyze data, and knowledge of data types, topics, and scientific challenges and approaches.
•Executes analytical procedures in the framework of a specific project work request.
•Creates or modifies scripts or software applications to support data management, data extraction and data analysis as required.
•Contributes to the interpretation of data analysis and to writing reports.
•Helps customers understand the data set and provide training and suggestions for improvement on the data request.
•Leverages communication and interpersonal skills and works with subject matter experts
•Presents findings in easy-to-understand terms for the business or clinical practice.

A bachelor’s degree in a relevant field such as engineering, mathematics, computer science, health science, or other analytical/quantitative and a minimum of three years of professional or research experience in data science will be considered.
 

The preferred candidate will possess a master’s degree or a PhD 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. Demonstrated ability to develop predictive models to address various business problems through leveraging advanced statistical modeling, machine learning, or data mining techniques. May provide consultative services to departments/divisions and committees. Demonstrated application of several problem-solving methodologies, planning techniques, continuous improvement 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. Interpersonal skills and time management skills are required. Requires strong analytical skills and the ability to identify and recommend solutions, advanced computer application skills and a commitment to customer service. Experience with data modeling and date exploration tools.

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 – 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. You’ll thrive in an environment that supports innovation, is committed to ending racism and supporting diversity, equity and inclusion, and provides the resources you need to succeed.