The University of Maryland Institute for Health Computing (UM-IHC) is a strategic collaborative between the University of Maryland, Baltimore (UMB) and the University of Maryland, College Park (UMCP), and the University of Maryland Medical System. Based in North Bethesda, MD, the institute focuses on artificial intelligence and advanced computing to further develop the field of precision medicine to improve well-being, quality of life, diminish disease, and enhance health outcomes for all citizens of Maryland and beyond.

Learn how we’re delivering a better state of care. 

We build upon our tradition of excellence in patient care and innovation, to be a national leader in the transformation of health care.  Proud to be recognized by Forbes to the America’s Best Large Employers for 2022, UMMS' flagship academic campus, the University of Maryland Medical Center in Baltimore, is recognized regionally and nationally for excellence in specialized care.

University of Maryland Medical System (UMMS) delivers comprehensive health care services throughout Maryland. UMMS physicians and patient care teams work hand-in-hand with University of Maryland School of Medicine specialists to provide primary and specialty care at more than 150 locations across the state, including a network of academic, community and specialty hospitals that together provide 25% of all hospital-based care in Maryland.  

Functioning as One UMMS will allow us to create greater opportunities for our team members, provide more comprehensive care for our patients, and support more communities across Maryland. It will reaffirm our values and allow us to leverage the benefits of being part of a stronger, statewide system. In the end, we are not creating a new system; we are strengthening the one we have built. Together, we will honor our past and simultaneously look to our future, not just as a health care system, but as vital members of our communities. Learn more about One UMMS at https://oneumms.org/

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.

Principal Responsibilities and Tasks
• 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.

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.

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.

All your information will be kept confidential according to EEO guidelines.