Senior Healthcare Data Scientist - 246766

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.

II. Principal Responsibilities and Tasks

• Support and drive analytic efforts designed around the organization’s strategic priorities and clinical / business problems.
• Develop and manage 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.
• Develop 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.
• Lead cross-functional design teams to drive disruptive innovation, which may translate into improved quality of care, clinical outcomes, reduced costs, temporal efficiencies and process improvements.
• Manage projects and initiatives for the medical system that include multi-disciplinary teams from technology, clinical and business groups.
• Mentor staff on effective problem-solving strategies and technical aspects of Machine Learning / AI, Statistics and Operations Research.
• Manage project plans and other required project documentation and provide updates to leadership as necessary.
• Develop and maintain relationships with business, IT and clinical leaders and stakeholders across the enterprise to facilitate collaboration and effective communication.
• Assist senior 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 senior 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.

III. Education and Experience

PhD degree in applied mathematics, data science, physics, computer science, engineering, statistics, economics, or a closely related field required; comparable work experience may be substituted for the PhD degree.

7+ years of industry experience in the following :

IV. Knowledge, Skills and Abilities