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 organizations 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 organizations 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.
• Preferred 3+ years of industry experience in the following:
• 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.