Cayuse, including system configuration, data management, reporting, technical support, integration with Workday, and migration of legacy research administration data into the University's enterprise data environment. As these systems mature, the position will expand to developing institutional datasets, dashboards, reports, predictive models, and other analytical tools that help leadership monitor research performance, identify opportunities, improve operational effectiveness, strengthen regulatory compliance, and support strategic investment in research.
Job Description
Examples of Work Performed:
- Data Engineering: Develop Extract-Transform-Load (ETL) scripts to extract data or clean data, automate tasks, supports business processes
- Liaise with vendors and central IT professionals to identify, propose, develop, and test integrations across enterprise systems
- Develop data dashboards and reports for ORED leaders and campus research stakeholders
- Communicate with research administration subject matter experts to define business needs and propose data-driven solutions
- Interact with technical experts to identify and implement cross-system integrations (e.g., moving data from Cayuse to Workday and vice versa)
- Collaborate across institutional units to leverage data resources and subject matter expertise in support of analytical and reporting needs
- Use data extraction tools (SQL/NoSQL/Python) to develop queries to answer research and analysis questions
- Develop and implement data solutions and analyses to help leaders and stakeholders understand, comply with, and thrive under the large, evolving, and complex federal rules and regulations related to grants and contracts.
Job Responsibilities:
Bachelor's degree—preferably in Data Science, Computer Science, Information Systems, or a related discipline. If the candidate holds a bachelor’s in an unrelated field but has substantial experience in related roles, they are encouraged to apply and should explain their qualifications and expertise as it relates to this position in their cover letter.
Applicants should submit a resume and a brief narrative (no more than two pages) describing the following:
- A complex data, systems, or reporting challenge you personally helped solve, including your specific role, the technologies you used, and the outcome.
- Why this position at the University of Mississippi interests you and how your experience would contribute to advancing the University's research enterprise.
The strongest applications will demonstrate thoughtful analysis, technical depth, and an understanding of how data can be used to improve organizational decision-making.
