Jobs · Information Technology · New York

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.

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