Data Scientist, Principal

4 weeks ago

Charlottesville, Virginia, United States The Rector & Visitors of the University of Virginia Full time
Job Summary

A principal data scientist will have a mastery of technical skills, advanced skills in managing, mentoring, and creating new approaches and tools for customers and the data science team to use.

They will have skills in developing effective processes, asserting an architectural vision, and fostering innovation in colleagues and peers.

Understands all phases of the analytic process, including data collection, preparation, modeling, evaluation, and deployment.

Explore and examine data from multiple disparate sources to identify, provide reporting on, and analyze trends in the data as well as regular reporting for assigned departments.

Establish links across existing data sources and find new, interesting data correlations.

Develop statistical, mathematical, and predictive models using strategic business understanding to build the algorithms necessary to ask the right questions and find the right answers.

Stay appraised of all assigned initiatives, providing reporting and analytics that will allow the group to make informed, data-driven decisions to meet business objectives.

Visualize and report data findings creatively in a variety of visual formats that appropriately provides insights to stakeholders.

Under general supervision, formulate and define analytic scope and objectives through research and fact-finding.

Is able to answer defined questions about health system functions/operations/populations using appropriate statistical techniques on available data.

Drives the collection of new data and the refinement of existing data for new purposes.

Analyze and interpret the results of experiments to create cost-effective and process-efficient alternatives, enhancements, or modifications.

Competent to work on most phases of data analysis and associated programming activities.

Manipulates high-dimensional data from a variety of sources.

Develops code and/or methods to integrate data to answer required questions.

Tests, debugs, and verifies analyses with managers and clinical leaders.

Lead analytics projects in concept formulation, determination of appropriate statistical methodology, data manipulation, research evaluation, and final research report.

Determines scope and timeline for the investigation of data sets to derive desired outcomes.

Policies and procedures for the workflow within the functional area of analysis are clearly understood and applied accurately assessing tradeoff and understanding effects on current automated systems.

Considers needs of customer in terms of method of information delivery, timeliness of information needs, and methods of information display such that customers can easily determine their necessary actions.

Iterates with customers and/or subject matter experts to continually increase sophistication of analysis and improve outcomes.

Selects and applies statistical/machine learning algorithms - Under general direction, sound solutions are reached through detailed analysis and accurate determination of causes of complex problems.

Regularly provides guidance and training to less experienced data analysts/scientists.

Statistical/machine learning knowledge enables appropriate coding assistance and instructions to junior level analysts.

Data analysis experience provides appropriate guidance to less experienced staff during analysis phase and validation that project requirements are being met.

Lead and coordinate a team of data scientists to solve difficult Health System data problems with multiple deliveries and data products.

Manage complex projects using systems engineering principles and best practice project management to successfully guide multiple contributors and satisfy multiple stakeholders.

Work with stakeholders and customers to define and develop requirements and designs for data products to solve health system problems.

Interact with both Analytics and Reporting Team scientists and external academic and commercial teammates to pursue and bring forth the best techniques for solving challenging data problems.

Regularly publish and present ART solutions to the Health System community at the national and regional venues, e.g. HIMSS.

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