Part-Time Faculty: SAL 601 M001: Intro to Sport Analytics (Fall 2026

Part-Time Faculty: SAL 601 M001:
Intro to Sport Analytics (Fall 2026)

Job Title:

Part-Time Faculty: SAL 601 M001:
Intro to Sport Analytics (Fall 2026)

Location:

Syracuse, NY

Campus:
Remote

Commitment to On-Campus

Experience:

Syracuse University is committed to delivering an exceptional student experience through vibrant, engaged campus communities. This position is based at the above campus location and requires regular in-person presence to support our students, collaborate with colleagues, and contribute to our thriving academic environment. Syracuse University values the collaboration, mentorship, and spontaneous connections that happen when our community works together on campus.

Remote work arrangements are limited in accordance with University policy.

Pay Range: $1,400 - $1,700 per credit hour

Pay Determination:
Salary offers at Syracuse University will be based on education, experience, and relevant skills, as well as the academic or professional discipline of the position in the context of the home department, school, or college. Salary offers may also be influenced by prior relevant work or industry experience, where applicable. Faculty pay ranges are for 8.5 months' salary unless otherwise specified.

FLSA Status:
Exempt

Hours:

As determined by department/chair

Job Type: Part-time

Rank: PTI/Adjunct

Unionized Position Code: UA

Job Description:

Falk College of Sport seeks a part-time instructor to teach SAL
601 M001, Intro to Sport Analytics (3 credits) in the Fall 2026 (8/24/26 to 10/22/26) semester. Course

Description:

This course covers a basic statistics review, visualization techniques in Tableau, a discussion of the Moneyball hypothesis, and an overview of the current state of player/team analytics in different sports.

Qualifications:

Bachelor's degree in Sport Analytics, Sport Management, Data Science, or a related field with a strong analytics background. Industry experience in business analytics within sport, ideally at the professional or elite collegiate level. Proficiency in Python and/or R for data analysis. Familiarity with Tableau, Power 31, or other dashboard tools. Knowledge of topics such as dynamic ticket pricing, sponsorship valuation, and social media analytics.

Responsibilities:
Developing and/or updating a class syllabus. Preparation of lectures, projects, or other student assignments. Maintaining regularly scheduled office hours. Presenting instruction based on the competencies and performance levels of the course. Meeting all designated class periods. Submitting completed mid-semester progress reports and final grades according to University regulations. Grading student assignments and exams in timely manner. Building a positive rapport with students and other faculty.

Application Instructions:
In addition to completing an online application, please attach a curriculum vitae and cover letter.