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Data Analyst I

University of Rochester Rochester, Vereinigte Staaten
21,78-30,53 USDpro Stunde
Arbeitsvertrag Vollzeit Arbeit vor Ort

Veröffentlichungsdatum: 01.09.2026

The Department of Public Health Sciences at the University of Rochester seeks a highly motivated individual to serve as a full-time predoctoral research associate (Data Analyst II) under the supervision of Dr. Elaine L. Hill, a health economist. The successful candidate will participate in NIH-funded research and join the Health and Environmental Economics Lab. RAs collect and organize data, conduct statistical analysis on large databases, contribute to manuscript writing (with the option for co-authorship), and provide other support associated with faculty research.

Responsibilities

Develops and supports ongoing research projects of faculty, compile, manipulate, and analyze data using various search engines and software packages; Develops, collects, manages, and manipulates complex datasets using a variety of tools and sources, including but not limited to Stata, SAS, R, or Python; Creates maps and links spatial data to health data; Analyzes and interprets data, statistics, and financial information; Collaborates with other members of the research team to advance research progress; Maintains effective communication with all members of the faculty, HEEL team, and outside collaborators; Partners with faculty on project management, managing near- and long-term priorities, exercising independent decision-making concerning the progression of research projects; Provides or facilitates guidance and training as needed to staff; Performs other duties as assigned

Requirements

Bachelor's degree in statistical analysis, data base management, or related discipline and 1 year experience with data analysis or customer resource management systems required; Or equivalent combination of education and experience; Strong attention to detail required; Strong organizational, data analysis and problem solving skills required

Nice to have

Familiarity with statistics and statistical analysis; Advanced knowledge of Microsoft Excel; Ability to visually portray data; Strong quantitative background; Excellent programming skills especially in Stata, with openness to learn SAS, Python, R or SQL; Ability to work independently to solve problems; Long-term interest in pursuing research in economics; Background in economics; Knowledge of GIS
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