Company Description
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.
Job Description

GENERAL SUMMARY

The Healthcare Data Scientist - Machine Learning/AI, Statistics, Operations Research position will join our Advanced Data Science group at the University of Maryland Medical System (UMMS) in support of its strategic priority to become a data-driven and outcomes-oriented organization. The successful candidate will have experience with Machine Learning/AI, Statistics and Operations Research and a passion for working with healthcare data. Previous experience with various computational approaches along with an ability to demonstrate a portfolio of relevant prior projects is essential. This position will report to the Director for Advanced Data Science & Consulting Services.

EDUCATION AND EXPERIENCE

• PhD degree in applied mathematics, data science, physics, computer science, engineering, statistics, economics or a related field required; comparable work experience may be substituted for the PhD degree.
• 3+ years of industry experience in the following preferred:
• Machine Learning/AI, Statistics or Operations Research.
• Programming with SQL, Python and R.
• Practical experience with 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.
• Text mining and Natural Language Processing (NLP) is preferred.

KNOWLEDGE, SKILLS AND ABILITIES

• Develop (from scratch) machine learning and/or deep learning approaches and algorithms to solve clinical and business (including operations, supply chain, human resources, finance) problems.
• Formulate and solve complex mathematical optimization problems using exact and heuristic approaches.
• Perform independent/unsupervised exploratory data analysis and advanced statistical analysis (e.g., regression analysis, cluster analysis, factor analysis, ANOVA).
• Design and prototype new application functionality for our products.
• Work with “real world” data including scrubbing, transformation, and imputation.
• Capable of artful storytelling and clearly presenting findings in oral and written format and through graphics to stakeholders at various organization levels.
• Knowledge of databases, data structures, data processing and data mining from large enterprise transaction systems (e.g., Epic, Infor/Lawson, McKesson HPM, Payer Claims or similar applications in healthcare or other industries).
• Effective at working independently and in collaboration with other staff members for software platform and web application development.
• Cooperatively and effectively work with people from various organization levels.
• Manage projects to meet organizational goals.
• Plan work, set clear direction, and coordinate own tasks in a fast-paced multidisciplinary environment, including triaging issues, identifying data anomalies, and debugging software.
• Able to compare, contrast, and validate work with keen attention to detail.
• Actively generate process improvements; support and drive change, and confront difficult circumstances in creative ways.
  Additional Information
  All your information will be kept confidential according to EEO guidelines.

Compensation

• Pay Range: $62.94-$67.96
• Other Compensation (if applicable):
• Review the 2024-2025 UMMS Benefits Guide

• Support analytic efforts designed around the organization’s strategic priorities and clinical/business problems.
• Develop predictive (machine learning and deep learning) and prescriptive (mathematical optimization and simulation) analytic models in support of the organization’s clinical, operations and business initiatives and priorities.
• 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 our 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.
  Qualifications