ABOUT THE POSITION
The Riverside University Health System Department of Public Health (PH) has an exciting opportunity for a PH Data Scientist.
The primary role of this position will be to perform data organization and visualization so that Epidemiologists and other team members can analyze and interpret data more efficiently. The incumbent, under general supervision, develops and applies methods to identify, collect, process, organize, and analyze structured and unstructured data using statistical prediction, inference and optimization; effectively communicates results to the Public Health Department; develops or assists in the development of new analytic methods, functions and data structures necessary to complete complex projects; performs other related duties as required.
The Public Health Data Scientist is an advanced journey level classification and reports to an appropriate supervisory or manager level position. Incumbents work independently while performing duties of considerable difficulty to complete moderately complex projects or major aspects of large/complex projects that may be department-wide in scope. Incumbents deploy techniques such as data extraction, transformation and loading; classical statistical analysis and machine learning, including predictive and prescriptive modeling and optimization; and data visualization to generate critical information and knowledge and effectively communicate findings to technical and nontechnical stakeholders to support data-driven program design, management and decision-making. Incumbents work with data sets characterized by large volume, moderate complexity and significant heterogeneity, integrating data from various sources, requiring direct collaboration with department IT staff to design and provide feedback on data systems and processes necessary to support the IT infrastructure and security compliance requirements.
The Public Health Data Scientist is distinguished from the Research Specialist II by the expertise and knowledge of the former in developing machine learning algorithms to analyze data, build predictive models and create visualizations and dashboards from which the latter uses to plan and design research projects, interpret findings using statistical or qualitative data analysis, and draw conclusions.
Meet the Team!
RUHS Public Health Department RUHS Public Health Department
EXAMPLES OF ESSENTIAL DUTIES
• Collaborate with Public Health Department and Epidemiology and Program Evaluation (EPE) Branch stakeholders to solicit, define and manage data science projects from conception through implementation, including identifying and developing statements of business problems; conduct exploratory data analysis and data mining; develop model specification requirements and conduct advanced statistical analyses.
• Use statistical tools and software to develop and present visualizations of findings and recommendations that can be used to support business decisions and allocation of resources.
• Work with Public Health Department and EPE Branch stakeholders to document business requirements and help frame business problems so that appropriate corresponding data science techniques can be identified and applied.
• Collaborate with Public Health Department and EPE Branch stakeholders to understand, identify and select available and relevant sources of data for use cases, including internal, external, structured, and unstructured data sources.
• Work with Public Health Information Technology team to support collection, integration and retention requirements for large sets of structured and unstructured data from various sources and consults with data engineers and architects on the design and architecture of relevant data systems and processes.
• Collaborate with other department data scientists, epidemiologists, research specialists, and IT staff to select, evaluate, improve, and document tools and systems to strengthen EPE Branch and other Public Health Department Branches analytic capacity.
• Independently conduct advanced analytical studies for the resolution of business problems and transfigures data into critical information by selecting and deploying appropriate advanced statistical techniques such as machine learning, bivariate and multivariate analyses, predictive/prescriptive analytics, and optimization.
• Plan, design and manage experiments, consumer surveys and other data collection projects to augment existing sources of data as necessary to solve business problems.
• Convey findings and conclusions of work orally, in writing, visually, in presentations, and by developing interactive tools as appropriate to communicate effectively with a wide range of audiences, including technical and nontechnical staff, stakeholders and members of the public.
• Work with EPE Branch staff to understand the implications of analyses and to ensure that findings are actionable and support data-driven programs, policies and operational decision-ma
Location: Riverside, CA
Posted: Sept. 15, 2024, 6:14 a.m.
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