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Data Scientist.UHHS ACO Operations Office-10702

University Hospitals – Shaker Heights, OH

DescriptionPosition Summary/Essential Duties: Responsible for executing projects that require the full data science pipeline including data integration of disparate and centralized data into data marts, data mining, statistical model development, report building and results presentation in support of UH Population Health operations. Works closely with senior leaders and colleagues to identify opportunities, set objectives, and formulate analytic strategies that result in measurable impact to University Hospitals Health System.
Key responsibilities include:
Application of Data Science and AI (45%)
  • Research, design, develop and implement statistical models, AI and advanced machine learning applications to support UH Population Health projects.
  • Develop data marts in SQL environments (on premise and cloud) that will help facilitate UH data science projects.
  • Develop the documentation and process to identify metrics, targets, weights and resulting clinical integration performance reports for network providers.
  • Be the technical lead focused on creative use of diverse data sources, such as electronic health record data, insurance claims data, scheduling and financial data, social determinants of health data, and any other relevant sources that help support UH Population Health strategy.
  • Develop new analytic methods and reporting systems to include visual dashboards and other direct-to-provider or direct-to-staff information.
  • Evaluate business performance on an ongoing basis and dynamically monitor critical operational measures related to shared savings arrangements, MSSP and BPCI programs, HRM initiatives, and other value-based programs.
  • Propose novel solutions to UH data science problems, develop solutions, demonstrate and evaluate the feasibility of solutions and, adapt and refine solutions into a real-world clinical care context.
  • Support the creation of analytics and scientific exploration related to risk modeling, financial performance and quality of care for managed populations.
  • In collaboration with information services, support the architecture of clinical integration approach for disparate data systems including use of data warehouse, external vendor supplied information and any future systems that are needed.
  • Support the Manager of Data Science & Analytics to coordinate statisticians, clinical researchers, providers, and developers who have received UH or CWRU support to develop data science products to improve health outcomes or health system operations.
  • Create technical interfacing between analytics/ dashboard directly to provider portal/ websites or mobile devices for up-to-date reporting for providers

Capacity Development (10%)
  • Mentor and support the training of new and existing staff in data science and advanced analytics.
  • Advise UH leadership on opportunities and gaps in the companys current capabilities across data science technology and infrastructure, and recommend plans for growth through adoption of new methods and/or technologies.
  • Develop documentation, software, support tools, and technology infrastructure to enhance the ability of analysts and operational leaders across the clinical enterprise to effectively and rapidly extract meaning from health care data.
  • Maintain fluency in existing and emerging data science technologies and complete online coursework or independent study to fill in gaps of knowledge as needed to manage and execute innovation projects.

Tools and product development: (20%)
  • Develop documentation, software, support tools, and technology infrastructure to enhance the ability of analysts and operational leaders across the clinical enterprise to effectively and rapidly extract meaning from health care data.
  • Maintain fluency in existing and emerging data science technologies and complete online coursework or independent study to fill in gaps of knowledge as needed to manage and execute innovation projects.
  • Oversee the development of novel data pipelines that integrate and normalize large data from a variety of sources (e.g., electronic health record, claims, wearable device, publicly available data, etc.) to enable learning health, machine learning model development, and deployment.
  • Run complex SQL queries and existing automation to correlate disparate data to identify questions and extract critical information
  • Work with quantitative sciences and clinical faculty to evaluate predictive models and innovation pilots and help disseminate results through peer-reviewed publications and at academic conferences.
  • Develop processes and tools to monitor and analyze analytical model performance and data accuracy; provide ad-hoc analysis and visualizations.

Knowledge sharing, translation, and scaling: (25%)
  • Engages with the data science team to promote collaboration and process learning. Will help team advance their capabilities using data science applications and technology.
  • Maintain expert knowledge of health system operations, clinically integrated networks, and accountable care organizations.
  • Write or develop a multitude of reports ranging from 1 page briefs to in-depth research reports and interactive dashboards. Must maintain writing skills at a high level of aptitude related to technical writing and academic writing.
  • Present findings and data-driven recommendations to health system leadership and partners.
  • Support the translation and appropriately champion advanced analytics results and capabilities (e.g. machine learning and natural language processing) to non-technical audiences.

QualificationsEducation/Expertise:
  • Bachelors degree in math, statistics, computer science, economics, sociology, public health, or related quantitative or social science discipline required.
  • Masters or PhD level work in analytics, statistics or related field preferred.
  • Minimum five years of experience working with complex analytic situations and big data environments.
  • Minimum four years of applied experience of statistics, machine / deep learning in a healthcare setting.

Experience & Knowledge:
  • Experience in one of the following: a patient care environment, population health improvement, or interpretation of health care data with statistical programming or data science tools.

Special Skills & Equipment Knowledge:
  • This position requires a self-starter who is adept at independent decision-making and is ideally suited for emerging leaders in health data sciences.
  • Extensive experience working with SQL and statistical programming languages (e.g., R, Python) and data science tools (e.g., Alteryx, SPSS, SAS, etc.) to analyze and visualize health care data.
  • Ability to develop data pipelines to support AI and machine learning model development.
  • Ability to learn new software and emerging technologies without extensive hands-on training.
  • Experience in visualization and reporting programs such as Power BI, Tableau, Microstrategy, etc.
  • Expertise in working with electronic health record and claims data and fluency working with ICD, CPT, LOINC, RxNorm and related standardized vocabularies.

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