Data Analyst II
University of Rochester · Rochester, New York Metropolitan Area · Yesterday
Information Technology$25.14–$35.24/hrFull-time
Job Location: 265 Crittenden Blvd, Rochester, New York, United States of America, 14642
Full-time, 40 scheduled weekly hours
Compensation Range: $25.14 - $35.24 (minimum and maximum for this role; individual salaries will be determined by factors including market data, education, experience, qualifications, expertise, and internal equity considerations)
Responsibilities
- Develop and support ongoing research projects of faculty, compile, manipulate, and analyze data using various search engines and software packages.
- Develop, collect, manage, and manipulate complex datasets using tools and sources including Stata, SAS, R, or Python.
- Create maps and link spatial data to health data.
- Analyze and interpret data, statistics, and financial information.
- Collaborate with other members of the research team to advance research progress.
- Maintain effective communication with faculty, HEEL team, and outside collaborators.
- Partner with faculty on project management, managing near- and long-term priorities, and exercising independent decision-making concerning research project progression.
- Provide or facilitate guidance and training as needed to staff.
- Other duties as assigned.
Requirements
- Bachelor's degree in statistical analysis, database management, or related studies and 3 years of data analysis or customer resource management systems experience (or equivalent combination of education and experience).
- Attention to detail, accuracy, and strong record-keeping skills.
- Data analysis and problem-solving abilities.
- Advanced Excel proficiency.
- 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.
Skills
- Background in economics recommended but not required; candidates with strong technical backgrounds seeking exposure to economics and data science are welcome.
- Knowledge of GIS is preferred.