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Data Analyst

Job Description

About Embry-Riddle Aeronautical University:

At Embry-Riddle, we take pride in our position as the world's largest and most comprehensive university dedicated to aviation and aerospace. Located in Daytona Beach, Florida, and Prescott, Arizona, our esteemed residential campuses offer a prestigious educational experience. However, our commitment to education knows no borders as our Worldwide campus expands our reach globally, providing a world-class education online and at approximately 110 locations across the United States, Asia, Europe, and Central and South America. This breadth of reach ensures that students can access our exceptional programs without geographical limitations.

With a history spanning nearly a century, we have continually adapted to the dynamic needs of the industries we support. In the Academic Year 2022-23, we welcomed over 11,100 students to our residential campuses and over 19,000 students at our worldwide campus.

Join our global community and embark on a journey of academic excellence and limitless possibilities. Employees working more than 30 hours a week can enjoy medical, dental and vision benefits, an amazing retirement plan with immediate vesting that includes a 6% gift and up to 4% match, free tuition for employees and their immediate family members, and a generous personal leave program. To find out more about our benefits and why ERAU has been named a “Great College to Work For” for 13 consecutive years, visit our careers page .

The Opportunity:

The Department of Institutional Research at Embry-Riddle Aeronautical University is currently recruiting for a Data Analyst to join the team. The Data Analyst will provide critical support in the facilitation of timely and accurate collection and retrieval of University data for official external reporting and internal decision-making. The Data Analyst will focus on data provision and analyses of academic course and faculty-related information, and will serve as a central data provider in a multi-campus environment, each with their own distinct profiles, reporting requirements, and decision-making needs.

Responsibilities include the following:
  • Develop a thorough understanding of university data sources and the flow of data throughout university systems. Understand the appropriate use of each.
  • Extract data from university enterprise and warehouse sources. Verify data accuracy; initiate and resolve data quality issues.
  • Use statistical software programming language to manipulate data and produce vetted, official datasets for multiple uses.
  • Maintain an understanding of external reporting requirements and activities such as IPEDS, Common Data Set, college directories/rankings, etc. Prepare and submit university summative data.
  • Develop and maintain reports and dynamic visualizations for university decision-making. Use appropriate applications and data to assist administrators, faculty, and staff in obtaining timely, accurate, and relevant information. Provide training for the use of self-service tools and dashboards to university personnel and/or teams.
  • Maintain up-to-date documentation on all projects, processes, and reports. Independently establish and manage project timelines.
  • Collaborate with other IR, IT, and Business Intelligence staff, as well as functional area subject matter experts, to clarify reporting methodologies, establish data standards and definitions, provide consistency and ensure accuracy in reporting.
  • Provide input for developing and improving systems and procedures. Represent IR on campus-wide committees as needed.
Qualifications
  • Bachelor's degree with an area of concentration in Data Science, Data Analytics, Statistics, Mathematics, or any field with a strong analytical focus.
  • At least one year of experience working with data analytics.
  • Experience working with a multitude of higher education divisions, especially Academic Affairs and Registrars.
  • Experience with a statistical programming software package (e.g. SPSS, SAS, R) and creating tabular/graphical representations of data. Preference for SPSS.
  • Experience with data analytics/visualization software, such as PowerBI, Tableau, or OBIEE.
  • Knowledge of relational and dimensional databases.
  • Understanding of a database querying language, such as SQL.
  • Knowledge of institutional research and its practices..

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