Athletics Data Science & AI Fellow

The Athletic Data Science & AI Fellow supports the daily functions of the Athletic Data Science & AI Lab. This position assists with data analysis, reporting, project coordination, documentation, and other lab-related responsibilities in support of departmental decision-making, innovation, and strategic initiatives. Salary Grade: 09 Please see Staff Compensation Structure for salary ranges., 1. Assist with collecting, organizing, reviewing, and maintaining data used to support athletic department projects and initiatives.

1. Assist with researching data sources, tools, and technologies that may support departmental priorities.
2. Assist with preparing reports, dashboards, summaries, and other data-related materials for review by department leadership and staff.
3. Support data analysis projects by gathering information, reviewing trends, and helping identify insights under the direction of the supervisor.
4. Monitor emerging trends in sports analytics, data science, and artificial intelligence and share relevant information with the supervisor as requested.
5. Assist athletic department personnel with basic data, analytics, and artificial intelligence-related questions, as directed by the supervisor.
6. Follow all department and University expectations related to data integrity, confidentiality, and security.
7. Assist with tracking analytics, data science, and AI projects assigned to the lab and provide routine updates on project status.
8. Assist with coordinating project timelines, meetings, and deliverables to support departmental objectives.
9. Assist with tracking lab-related expenses, inventory, and equipment, as directed.
10. Assist with maintaining lab procedures, documentation, and resources, with emphasis on data integrity, confidentiality, and security.
11. Assist with communication and coordination between the athletic department, campus partners, and external partners on data science, analytics, and artificial intelligence initiatives.
12. Assist with onboarding, training, and providing general project guidance to undergraduate student workers assigned to the lab.
13. Help ensure student workers understand expectations related to confidentiality, data security, and accurate timesheet submission.
14. Ensure all assigned tasks follow department, University, Southeastern Conference, and NCAA rules and regulations.
15. Other duties as assigned in support of data science, analytics, artificial intelligence, departmental reporting, or other lab functions. The above essential duties are representative of major duties of positions in this position. Specific duties and responsibilities may vary based upon departmental needs. Other duties may be assigned to the above consistent with the knowledge, skills and abilities required for the job. Not all of the duties may be assigned to a position.

Bachelor’s Data Science, Computer Science, Statistics, Business Analytics, Sport Management, or related field., 1. Working knowledge of Python, R, SQL, or similar tools.

1. Familiarity with data visualization tools such as Tableau or Power BI.
2. Familiarity with basic statistical analysis, machine learning concepts, or data modeling.
3. Prior experience in sports analytics, data analysis, or a research lab environment.

4. Interest in data science, analytics, and artificial intelligence within college athletics. Knowledge, Skills, and Abilities:

5. Basic data entry and/or word processing skills.
6. Ability to sort, check, count, and verify numbers.
7. Records maintenance skills.
8. Knowledge of payroll policies and procedures.
9. Knowledge of university accounting procedures involving procurement, travel, and/or employment.
10. Ability to prepare routine administrative paperwork.
11. Ability to perform simple accounting procedures.
12. Ability to analyze and solve problems.
13. Knowledge of cash management principles and/or procedures.
14. Ability to handle sensitive information.
15. Knowledge of NCAA and SEC rules and regulations. Working Conditions and Physical Effort

• Work is normally performed in a typical interior/office work environment.
• No or very limited exposure to physical risk.
• No or very limited physical effort required.