The Healthcare Data Scientist role will join our talented Advanced Data Science & Consulting Services group at the University of Maryland Medical System (UMMS) in support of its strategic portfolio of novel and innovative solutions and services. The successful candidate will have 3+ years of experience with the above listed domains and a passion for working with healthcare data and problem sets. Previous experience with various computational approaches along with an ability to demonstrate a portfolio of relevant prior projects is essential. This role will primarily focus on opportunities and problems sets involving Operation Research - Mathemtical Optimization, Simulation, and Machine Learning. This position will report to the Principal Data Scientist.

• Will engage in creating problem solving using Machine Learning, Artificial Intelligence, and Operations Research - Mathematical Optimization and Simulation.
• Anticipates data and science-related bottlenecks, provides escalation management, anticipates and makes trade-offs, and balances clinical and business needs versus scientific and technical constraints.
• Partners with clinical and business stakeholders in the development of inference-driven features.
• Actively identifies existing and new features, which could benefit from predictive modeling and implementation of predictive models.
• Actively identifies and resolves strategic issues that may impair the team’s ability to meet strategic, scientific, and technical goals.
• Partners with stakeholders to create, maintain, and prioritize the hypothesis and experimentation backlog.
• Takes large, scientifically complex projects and break them down into manageable hypothesis and experiments to inform, functional specifications, then deliver features in a successful and timely manner.
• Develops and manages 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.
• Deploys solutions so that they provide actionable insights to the organization and are embedded or integrated with application systems.
• Support and drive analytic efforts designed around organization’s strategic priorities and clinical/business problems.
• Builds and extends our analytics portfolio supported by robust documentation.
• Works with autonomy to find solutions to complex problems using open source tools and in-house development
• Stays abreast of state-of-the-art literature in the fields of operations research, statistical modeling, mathematical optimization, simulation, machine learning and simulation.
• Works with the analytics team and clinical/business stakeholders to develop pilots so that they may be tested and validated in pilot/incubator settings.
• Assists senior leadership with strategies for scaling successful projects across the organization and enhances the analytics applications based on feedback from end-users and clinical/business consumers.
• Develops strategic, tactical and operational presentations that summarize the results of predictive and prescriptive analytics projects in support of robust strategies for the organization.
• Ability to formulate and solve complex mathematical optimization problems using exact and heuristic approaches.
• Ability to develop complex process models using discrete-event-simulation.
• Proven programming skills in Python; ability and experience to participate in software platform and web application development.
• Proven communications skills – Effective at working independently and in collaboration with other staff members. Capable of artful storytelling and clearly presenting findings in oral and written format and through graphics.
• Proven analytical skills – Able to compare, contrast, and validate work with keen attention to detail. Skilled in working with “real world” data including scrubbing, transformation, and imputation.

• Master’s degree in industrial engineering, computer science, applied mathematics, physics, engineering, or a related field required; PhD degree highly preferred. Extensive work experience and prior proven experience in the desired technical thought leadership may be substituted for education.
• Strong background in computer science, operations research, industrial & systems engineering statistics or a physical engineering discipline.
• 3+ years of Machine Learning/Artificial Intelligence, Operations Research - mathematical optimization & simulation, etc.
• Proven prior experience with Python and R is a must (experience with tools such as WEKA, RapidMiner, or other open source tools are strongly preferred).
• Ability to develop and apply computational algorithms and AI methods to healthcare data (including, but not limited to data from electronic medical record, business transaction systems, and supply chain).
• Proven prior experience in developing and deploying healthcare-relevant predictive and prescriptive models.
• Proven prior practical experience with formulating and solving mathematical (deterministic and stochastic) optimization problems and simulation; prior experience in Arena, FlexSim or similar environments.
• Experience with discrete-event-simulation preferred.
• Proven experience with SQL.
• Proven experience and strong development skills in Python.
• Proven experience with combining analytic methods and advanced data visualizations.
• Expert ability to break down and clearly define problems.