Optimatch Scheduling Analytics & Predictive Modeling Support Intern

Spring 2026 Internship – Optimatch Scheduling Analytics & Predictive Modeling Support

Position Summary

The Optimatch Product Analytics & Predictive Modeling Intern supports the continued development of Optimatch, a data-driven platform designed to forecast attendance and viewership and generate optimized, logistics-based scheduling recommendations. 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

Qualifications

• Currently pursuing or recently completed coursework in data science, analytics, statistics, computer science, or a related quantitative field

• Demonstrated experience building predictive models (regression, classification, forecasting, or machine learning)

• Proficiency in Python and/or R for data analysis and modeling

• Experience cleaning, joining, and managing large datasets

• Familiarity with model evaluation techniques and performance metrics

• Ability to work independently in complex analytical environments

• Interest in sports analytics, predictive modeling, and analytics product development

Preferred but Not Required

• Experience contributing to analytics-driven applications or tools

• Familiarity with basic front-end concepts or frameworks (e.g., Streamlit, Dash, Shiny, or similar)

• Experience with APIs, data pipelines, or automated workflows

• Familiarity with Git or version control systems

• Interest in optimization or scheduling problems

To apply email your resume and cover letter to jmccauley@collegiatesmg.com