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

Company:  University of Maryland Medical System
Location: North Bethesda
Closing Date: 02/11/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description
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.

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.

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