Healthcare Data Scientist – Machine Learning/AI, Statistics Operations Research

The University of Maryland Medical System (UMMS) is an academic private health system, focused on delivering compassionate, high quality care and putting discovery and innovation into practice at the bedside. Partnering with the University of Maryland School of Medicine, University of Maryland School of Nursing and University of Maryland, Baltimore who educate the state’s future health care professionals, UMMS is an integrated network of care, delivering 25 percent of all hospital care in urban, suburban and rural communities across the state of Maryland. UMMS puts academic medicine within reach through primary and specialty care delivered at 11 hospitals, including the flagship University of Maryland Medical Center, the System’s anchor institution in downtown Baltimore, as well as through a network of University of Maryland Urgent Care centers and more than 150 other locations in 13 counties. For more information, visit www.umms.org.

Serve as member of Advanced Data Science group to support UMMS’s strategic priority to become a data-driven and outcomes-oriented organization.  Principal responsibilities and tasks include:

 

• Support analytic efforts designed around the organization’s strategic priorities and clinical/business problems, including operations, supply chain, human resources, and finance.
• Develop predictive (machine learning and deep learning approaches/algorithms) and prescriptive (mathematical optimization and simulation) analytic models in support of the organization’s clinical, operations and business initiatives and priorities.
• Formulate and solve complex mathematical optimization problems using exact and heuristic approaches.
• Perform exploratory data analysis and advanced statistical analysis (e.g., regression analysis, cluster analysis, factor analysis, ANOVA).
• Design and prototype new application functionality for products.
• Deploy solutions so that they provide actionable insights to the organization and are embedded or integrated with application systems.
• Work with the analytics team and clinical/business stakeholders to develop pilots so that they may be tested and validated in pilot/incubator settings.
• Perform statistical analysis to evaluate primary and secondary objectives from such pilots.
• Support development of strategic, tactical and operational presentations that summarize the results of predictive and prescriptive analytics projects in support of robust strategies for the organization.
• Build and extend analytics portfolio supported by robust documentation.
• Work in a team to drive disruptive innovation, which may translate into improved quality of care, clinical outcomes, reduced costs, temporal efficiencies and process improvements.
• Assist leadership with strategies for scaling successful projects across the organization, and enhance the analytics applications based on feedback from end-users and clinical/business consumers.
• Assist leadership with dissemination of success stories (and failures) in an effort to increase analytics literacy and adoption across the organization.
• Work with autonomy to find solutions to complex problems using open source tools and in-house development.
• Stay abreast of state-of-the-art literature in the fields of machine learning/AI, operations research, statistical modeling, statistical process control and mathematical optimization.
• Up to 5% domestic travel.

 

 

Minimum Requirements

• Master’s degree in Applied Mathematics, Data Science, Physics, Industrial Engineering, Computer Science, Statistics, Economics or a related field.
• Two (2) years of relevant work experience to include:• Machine Learning/AI, Statistics or Operations Research.
• Programming with SQL, Python and R.
• Machine learning/AI problems, or formulating and solving mathematical (deterministic and stochastic) optimization problems and simulation, or performing advanced statistical analysis.
• Developing and applying computational algorithms and statistical methods to healthcare data (including, but not limited to, data from electronic medical record, financial management, human resources, quality and supply chain).
• Developing and deploying healthcare-relevant predictive and prescriptive models.
• Combining analytic methods and advanced data visualizations.

 

Compensation:             $125,000 to $145,000 per year

 

Benefits:  Health, vision, dental, and life insurance, 403(b) retirement plan, paid time off, educational assistance, employee assistance program, and employee discounts.

 

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