Job Category: Exempt

PCLS: 30166

Salary Grade: I

Summary

This classification is responsible for merging and analyzing data from different systems to provide data-informed decision-making support to university executive leaders. Incumbents leverage complex data sets using advanced analysis techniques such as predictive modeling, random forests, and multi-level models to support the University’s goals. Incumbents apply this technical knowledge to communicate in both written and oral forms to other units and University leadership as a collaborating consultant. Incumbents provide accessible, action-oriented insights that optimize and encourage strategic, data-driven decisions by program administrators/executives.

Reporting and Supervisory Responsibilities

This classification typically has no supervisory responsibilities, but may train or guide other employees, interns, or students.

Typical Functions

1. Create new models of analysis that leverage University data towards optimization, intentionality, and strategic decision making.
2. Collaborate with each unit’s program administrator and stakeholders to develop the context around the student collaboration data.
3. Build strong relationships and communicate with program administrators and stakeholders.
4. Identify and pursue opportunities to educate and train in how advanced analytical techniques can strengthen strategic decision making, specifically, in University leadership.
5. Consult with USU leadership to provide accessible and action-oriented deliverables.
6. Serve as a point of contact and liaison for strategic-decision making within USU.
7. Create, maintain, and execute a cascading action plan to merge, clean, and analyze large data sets from disparate sources.
8. Interpret, analyze, and synthesize analytical data to present as executive summaries.
9. Design and distribute leadership-empowering consultations/trainings in data utilization to program leaders and executives.
10. Support and collaborate with institutional partners across campus.
11. Oversee preparation and distribution of public scholarship and peer-reviewed data science.
12. Pursue grant-funding opportunities in collaboration with division leadership

Knowledge, Skills, and Abilities

1. Ability to utilize technical knowledge in data analysis such as: latent analyses, multiple regressions, multilevel analyses, parametric and non-parametric analyses, random forest algorithms, and other prediction based models.
2. Ability to utilize multiple software packages such as R, SPSS, Mplus.
3. Ability to visualize data using programs such as R ggplot & plotly, InDesign, and Microsoft Office Suite.
4. Ability to collect data using programs, such as Qualtrics or RedCAP.
5. Ability to consult leadership in data optimization and utilization.
6. Verify verbal and written communication skills in both academic and interpersonal settings.
7. Capability to use soft-skills to further University data optimization.
8. Ability to collaborate with and train colleagues and program leadership to better utilize data.
9. Capacity to build and deliver trainings effectively.
10. Ability to interpret and synthesize large data sets.
11. Drive to stay educated in the field of data science, predictive analytics, and higher education program evaluations.
12. Ability to serve as a diplomatic liaison/consultant in technical data analysis to all of USU.
13. Ability to recognize current trends in data sets and build strategic responses.

Minimum Qualifications

Master’s degree with two years relevant experience or doctoral degree.

Work Environment and Physical Requirements

Employees work indoors and are protected from weather and/or contaminants, but not, necessarily, occasional temperature changes. The employee is regularly required to sit and often uses repetitive hand motions.

Disclaimer

This position description indicates the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive list of all duties, responsibilities, and qualifications required of employees assigned to the position.