Data Analyst and Evaluation Specialist

Role Overview

The Data Analyst and Evaluation Specialist supports the maintenance of data infrastructure while providing data analysis and insights to support operational and strategic decision making pertinent to student success.

What You Will Do

Develops Power BI dashboards, visualizations, reports, and analytical products supporting real-time monitoring, strategic planning, operational decision making, accountability reporting, portfolio level insights, and articulation of the student experience.

Why It Might Be a Fit

The Specialist makes recommendations on how university level data informs the department’s strategic direction, and provides evidence-based direction on KPIs for areas across the department.

Requirements

• Bachelor’s degree in business, Statistics, Economics, Data Analytics, or a combination of equivalent experience and education.
• At least 3 years of experience in a data analysis and/or research role – working with complex datasets.
• Strong educational and professional background in data management, statistical analysis, associated computer applications, program evaluation, and related applied social research methods (qualitative and quantitative methods):
• Python and/or R experience with manipulating, transforming and visualizing data
• Creation and maintenance of reports and dashboards in Power BI utilizing various data connections
• Experience establishing data connections using APIs
• Experience working with relational databases and creating queries in SQL
• Advanced knowledge of Excel (functions/formulas, pivot tables, Power Query, and macros)
• Experience within an educational setting strongly preferred.
• Experience developing assessment/evaluation processes and continuous improvement plans/approaches for both large- and small-scale programs and initiatives strongly preferred.
• Experience developing surveys for data collection and performing data analysis
• Experience utilizing Qualtrics
• A record of and commitment to participating in ongoing learning and engagement in the areas of equity, diversity, inclusion, anti-racism, accessibility and indigenization.
• Demonstrated leadership and guidance in using descriptive and inferential statistics to understand trends, patterns, and dependencies with respect to a variety of strategic issues.
• Experience with data governance and privacy is highly preferred.
• Knowledge of barriers to student success (systematic, historic, issues of access) for underrepresented or non-traditional students and students who are academically at risk.
• Knowledge of how these barriers may impact data collection techniques and overall program evaluation practices.
• Strong understanding of the assessment/evaluation process including instrument design.
• Strong knowledge of data management, manipulation, interpretation, and analysis skills using statistical analysis or data transformation tools including Excel, SQL, Python, and/or R.
• Strong demonstrated ability to create clear and precise process documentation.
• Experience working within collaborative and document management environments (e.g., Microsoft Teams, SharePoint).
• Proven ability to deliver timely, accurate, comprehensible, professional-quality data analytical reports.
• Strong organizational skills coupled with the ability to handle multiple tasks, meet deadlines, and excel in a fast-paced environment characterized by changing priorities.
• Excellent consultation and communication skills: ability to converse articulately with university administrators and other campus stakeholders including ability to translate analysis results to a non-technical audience.
• Ability to use descriptive and inferential statistics to analyze data; and knowledge of various methodologies to gather data (surveys, interviews, focus groups, community forum, literature reviews, environmental scans; situational analysis, needs assessment, etc.).
• Ability to work independently and as part of a team.
• Working knowledge of GenAI concepts and applications as they relate to data analytics, reporting, and decision support in higher education, including an understanding of data readiness, ethical considerations, privacy implications, and limitations of GenAI as a tool.

Benefits

• Dental insurance
• Vision insurance
• Health insurance
• Life insurance
• Disability insurance
• Paid vacation
• Paid sick leave
• Paid holidays
• Retirement plan
• Employee assistance program
• Flexible work arrangements
• Professional development opportunities
• Wellness programs
• Employee recognition and reward programs

Tagged as: Data Analysis