Graduate Assistant - Sports Analysis 2025-2026

Posting Details

Job Summary/Basic

Function

In alignment with our mission to integrate data-driven decision-making in athletics, we seek a

Graduate Assistant (GA) in Sports Analytics

to support sports teams by applying data science techniques to real-world performance analysis. The GA will work closely with coaching staff, athletes, and analysts to provide actionable insights that enhance team strategy, player development, and injury prevention.

Essential Job Functions/Responsibilities

Data Management & Analysis:

Collect, clean, and analyze sports-related data from various sources, including performance tracking systems, game statistics, and wearable technology.

View Full Description

Posting Details

Job Summary/Basic

Function

In alignment with our mission to integrate data-driven decision-making in athletics, we seek a

Graduate Assistant (GA) in Sports Analytics

to support sports teams by applying data science techniques to real-world performance analysis. The GA will work closely with coaching staff, athletes, and analysts to provide actionable insights that enhance team strategy, player development, and injury prevention.

Essential Job Functions/Responsibilities

Data Management & Analysis:

Collect, clean, and analyze sports-related data from various sources, including performance tracking systems, game statistics, and wearable technology.

Predictive Modeling & Insights:

Develop statistical models to assess player performance, injury risk, and game strategy optimization.

Visualization & Reporting:

Create dashboards and reports using tools like Python, R, SQL, Tableau, or Power BI to communicate key findings.

Collaboration with Sports Teams:

Work closely with coaches, players, and athletic staff to translate data insights into practical recommendations.

Performance & Strategy Evaluation:

Assist in game preparation and post-game analysis by identifying key trends and patterns.

Ethical Data Usage:

Maintain confidentiality and adhere to best practices in sports data ethics and athlete privacy.

Additional Duties:

Support other sports analytics projects and initiatives as assigned.

Learning Objectives:

1. Engage collaboration skills with other data science majors and the Maryville sports community.

2. Coordinate with sports analytics companies in the region where we have developed a collaboration to answer questions posed by them.

3. Gain knowledge and technical competence using statistical software such as R and R Studio, PowerBI, and Python.

4. Determine and perform the appropriate statistical analysis via critical reasoning in problem-solving.

5. Communicating statistical data to demonstrate the applied theoretical concepts in attempting to solve a problem.

6. Relate the changes in “traditional” and new statistical data in sports.

7. Create analytics to communicate and use statistical data.

8. Apply analytics in assessing a data set in assembling a team to use in a long-term assessment.

Compensation:

Stipend for the

academic year

: $3000

Tuition award for the

academic year:

12 credits

The award is based on 20 hours per week for 15 weeks each semester. It is expected that students earn their credit hours in the fall and spring semesters by being enrolled in a minimum of 6 credit hours each semester. Credits must be earned by May 31 each year. Tuition waiver does not cover fees, private music lessons, books, or OneCard charges. Students will receive ½ of their annual stipend during the Fall semester and ½ of their annual stipend during the Spring semester. Each semester, the stipend will be divided into 8 payments. Fall stipends are paid on or about September 15-December 31. Spring stipends are paid on or about January 31-May 15

Minimum Qualifications

Bachelor's degree required

Must be be enrolled in one of the following graduate programs at Maryville University

a. Masters in Business Administration, Masters in Education

b. Masters in Data Science, Masters in Actuarial Science, Occupational Therapy

Proficiency in

data analysis tools

such as Python, R, SQL, or Tableau.

Ability to communicate technical findings effectively to

non-technical stakeholders

(e.g., coaches, athletes).

Preferred Qualifications

Strong understanding of

statistical modeling and data visualization techniques

.

Experience working with

sports data, performance tracking technologies, or analytics in an athletic setting

.

Familiarity with

sports science concepts, biomechanics, or player performance metrics

.

Strong problem-solving skills and ability to work in a

fast-paced, team-oriented environment

.

Physical Demands

Open Until Filled

Yes

Special Instructions to Applicants

An offer of employment is contingent upon successful completion of a background screening.

Applicants requiring University sponsorship to obtain employment authorization will not be considered for this position.

Maryville University is committed to a policy of equal opportunity and prohibits discrimination on the basis of age, disability, gender, genetic information, marital status, national origin, race/color, religion, sex, sexual orientation, veteran status, or any other status protected by law. This extends to all aspects of the employment relationship, including recruiting, hiring, training, on-the-job treatment, promotion, layoff, and termination.

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