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

Overview

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.

In Short

• Support analytic efforts designed around the organization’s strategic priorities and clinical/business problems.
• Develop predictive and prescriptive analytic models in support of the organization’s initiatives.
• Deploy solutions to provide actionable insights to the organization.
• Work with analytics team and stakeholders to develop pilots for testing and validation.
• Perform statistical analysis to evaluate objectives from pilots.
• Support development of presentations summarizing analytics project results.
• Build and extend the analytics portfolio with robust documentation.
• Drive disruptive innovation to improve quality of care and reduce costs.
• Assist leadership with scaling successful projects across the organization.
• Stay abreast of literature in machine learning/AI and operations research.

Requirements

• PhD in applied mathematics, data science, or related field required.
• 3+ years of industry experience in Machine Learning/AI, Statistics, or Operations Research.
• Programming experience with SQL, Python, and R.
• Practical experience with machine learning problems and statistical analysis.
• Experience developing healthcare-relevant predictive and prescriptive models.
• Knowledge of databases and data processing from large enterprise systems.
• Effective communication skills for presenting findings to stakeholders.
• Ability to work independently and collaboratively in a fast-paced environment.
• Project management skills to meet organizational goals.
• Attention to detail and ability to generate process improvements.

Benefits

• Competitive salary range.
• Comprehensive benefits package.
• Opportunities for professional development.
• Supportive work environment focused on innovation.
• Access to cutting-edge research and technology.