As part of a collaborative team, the Data Analysis Specialist builds relationships with faculty, students, and staff to support teaching, learning, and research on campus. Specifically, the Data Analyst Specialist will connect with departments and programs to identify existing data analysis and data management needs on campus. Based on campus needs, the incumbent will develop services and educational programming.

This is a union position. Employees working in this position are covered by the collective bargaining agreement between the University and Service Employees International Union (SEIU) Local 888.  Provisions related to wages, benefits and other terms of employment are contained in the agreement.

The hiring range is 83,800 – 92,500

The Data Analysis Specialist is primarily an on-site position, with the option to work from home two days per week.

For full consideration, please submit your cover letter and resume/CV by October 17, 2025.

• Consults with faculty, students, and staff on projects involving data analysis, data visualization, software use, programming needs, and research data management. 40%

• Develops educational support systems for data analysis and research data management: 40%
  • Designs and delivers workshops on data collection, wrangling, analysis, visualization, and interpretation methods and related software and programming languages;
  • Develops instructional programs and learning materials in a variety of formats and for researchers at different levels of experience.
  • Develop and deliver resources and guidelines on file and research data management practices, tools, and repositories

• Participates in and contributes to committees and work groups of the Library and the University. 10%
• Furthers knowledge in data services through: 10%
  • attending, participating in, or contributing to trainings, conferences, webinars, and other types of professional development.
  • maintaining knowledge of best practices, developments, and trends in data services.

Qualifications

• Education: A graduate degree in a science field or related quantitative discipline is required. Preferred: Research experience in the sciences.
• Work Experience: 3-5 years of total related work experience
• Applied use of multiple programming languages including Python and R
• Data visualization tools like ggplot2 and matplotlib
• Experience or strong interest in teaching. ​

Familiarity with:

• Matlab
• Version control systems such as git/GitHub
• LaTeX typesetting
• Unix Shell Scripting (Bash)
• Research data management including work with sensitive or confidential information

Equal Opportunity Statement