Scheduling & Predictive Modeling Support Intern

Fall 2027 Internship – Scheduling & Predictive Modeling Support

Position Summary

The Scheduling & Predictive Modeling Intern supports the continued development of OptiMatch, CSMG’s data-driven platform designed to forecast attendance and viewership and generate optimized, logistics-based scheduling recommendations. The platform leverages historical performance, attendance, media viewership, social engagement, and market-based data to project matchup value and support strategic decision-making across collegiate and professional sports. This role is intended for a highly qualified analytics intern with experience in predictive modeling and an interest in building analytics-driven products, including client-facing user interfaces.

Key Responsibilities

• Support development and refinement of predictive models for attendance and viewership

  ● Assist with feature engineering, model training, validation, and performance evaluation

  ● Support translation of model outputs into inputs suitable for a client-facing UI Assist with defining model inputs, outputs, and constraints used in scheduling logic

  ● Support development of logistics-based scheduling logic incorporating geography, timing, and market variables

  ● Build, clean, and maintain datasets used in Optimatch workflows

  ● Perform data scraping and automated data collection from public and licensed sports data sources

  ● Support integration of analytics workflows into a user-facing application

  ● Document model assumptions, data pipelines, and analytical logic

  Responsibilities will vary across roles. Additionally, there will be an opportunity for all of our interns to collaborate across departments and gain experience in multiple areas of interest.

Qualifications

• Pursuing a bachelor’s degree in Business Analytics, Marketing Analytics, Data Science, Economics, Statistics, or related fields

  ● Demonstrated interest in or experience with analytics, business intelligence, media analytics, sports business, or sports media

  ● Experience working within collegiate athletics or other sports properties, agencies, or media organizations

  ● Strong understanding of collegiate and professional sports ecosystems, including scheduling, media rights, viewership, attendance, and fan engagement metrics

  ● Strong foundation in Microsoft Excel (financial modeling, scenario analysis, valuation frameworks) and data analysis workflows

  ● Experience with Tableau, Canva, Power BI, and/or Google Suite

  ● Foundational knowledge of SQL, RStudio and/or Python (Advanced knowledge of and demonstrated history within these platforms preferred)

  ● Familiarity with machine learning concepts and forecasting methodologies

  ● Exposure to predictive modeling techniques (regression, forecasting, back-testing)

  ● Ability to structure large datasets with high accuracy

  ● Strong attention to detail

  ● Ability to translate technical outputs into executive-ready storytelling using dashboards

  Applications will be reviewed on a rolling basis. To apply, please email your resume and a detailed cover letter to Shane Halpin at shalpin@collegiatesmg.com.