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Internship Math Sports Jobs (NOW HIRING)

The University of Alabama

Supervise practicum and internship experiences as needed * Collaborate in further development of ... The College of Education is also home to the No. 1 competitive adaptive sports program in the ...

Enterprise Elementary

School Psychologist

Redding, CA · On-site

$87K - $133K/yr

From music and fine arts, to sports, science, mathematics, and honors and advanced classes, we are ... Resume Comments and Other Information Willing to consider Internship. The District will contribute ...

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Internship Math Sports information

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How much do internship math sports jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for internship math sports in the United States is $16.33, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What is an internship math sports?

Internship Math Sports positions are temporary roles designed for students or recent graduates interested in applying mathematical concepts to sports analytics or sports management. These internships typically involve analyzing sports data, creating statistical models, and assisting with research projects related to team performance, player statistics, or game strategies. Interns may work with professional sports teams, college athletic departments, or sports technology companies. The goal is to gain hands-on experience in using math to solve real-world problems in the sports industry.

What do internship math sports interns do?

In a Math Sports internship, interns are often involved in analyzing sports data, developing statistical models to evaluate player or team performance, and assisting with research for game strategy or player scouting. They may use programming languages like Python or R to handle large datasets and present findings to coaches or analysts. Collaboration with other interns and sports professionals is common, providing exposure to real-world applications of mathematical concepts in the sports industry.

What are the key skills and qualifications needed to thrive as an internship math sports?

To thrive in a Math Sports Internship, you need strong quantitative analysis, problem-solving skills, and a background in mathematics, statistics, or a related field. Familiarity with data analysis tools like Excel, R, or Python, and experience with sports analytics platforms are typically required. Effective communication, attention to detail, and teamwork help interns interpret and present data-driven insights to coaches or analysts. These skills are crucial for transforming complex data into actionable strategies that can improve team performance and decision-making in the sports industry.

What is the difference between Internship Math Sports vs Internship Data Analysis?

AspectInternship Math SportsInternship Data Analysis
Required CredentialsMathematics or Sports Science backgroundStatistics, Data Science, or related fields
Work EnvironmentSports teams, athletic organizations, sports analytics firmsCorporate, tech companies, research institutions
Industry UsageSports performance, athlete analytics, game strategyBusiness insights, market research, data-driven decision making

Internship Math Sports focuses on applying mathematical skills within sports contexts, such as athlete performance analysis and game strategy. In contrast, Internship Data Analysis involves analyzing data across various industries to inform business decisions. Both roles require strong analytical skills but differ in industry focus and application areas.

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Internship Math Sports jobs near you
Infographic showing various Internship Math Sports job openings in the United States as of August 2026, with employment types broken down into 72% Full Time, 26% Part Time, 1% Contract, and 1% Nights. Highlights an 97% Physical, and 3% Remote job distribution, with an average salary of $33,957 per year, or $16.3 per hour.

Junior Software Engineer (AI-Forward)

Texas Sports Academy Main

Austin, TX • On-site

Full-time

Re-posted 25 days ago

Job description

As a Junior Software Engineer with Texas Sports Academy, you'll help build the software that runs our school, student records, academic mastery tracking, training data, parent portals, admissions, and the AI-powered tools our guides and coaches use every day. This is an early-career, AI-forward seat. You'll work directly with the founders and senior engineers, ship code every week with AI in your loop, and grow into the LLM-powered features that make our school feel nothing like a traditional school.

What You Will Be Doing
  • Building and shipping product features across the full stack every week, with AI coding tools running alongside you.
  • Contributing to real LLM-powered product features: tutoring agents, parent-facing copilots, coach-facing dashboards, retrieval over student data, and the evals behind them.
  • Working directly with the founders and senior engineers on scope and trade-offs, no PM layer in between.
  • Picking up ownership of smaller systems end-to-end and growing into bigger ones.
  • Running your own AI coding workflow, prompts, subagents, custom tools, MCP servers, and getting sharper at it every week.
  • Writing evals and regression tests for AI features the same way you'd write unit tests for classical code.
What You Will NOT Be Doing
  • Pretending AI is optional. If you're not already coding with Claude Code, Cursor, Codex, or an equivalent agent loop, this role is not for you.
  • Sitting in status meetings all day. Few meetings, more shipping.
  • Working on a narrow slice of a giant codebase.
  • Waiting around for tickets. You'll be in the room when we decide what to build.
Key Responsibilities
  • Ship production code and AI features that real students, parents, and staff rely on every day.
  • Own smaller systems and features end-to-end as you ramp up.
  • Move fast. Features go from idea to production in days, not quarters, without breaking things.
  • Level up your AI-engineering chops alongside a senior team.

Requirements

  • Bachelor's or master's degree in Computer Science, Engineering, Math, or Physics.
  • 0 to 2 years of full-time engineering experience. Strong internships, side projects, and shipped personal work count.
  • Daily, fluent use of AI coding tools (Claude Code, Cursor, Codex, Windsurf, Aider, or equivalent) as your default way of writing software.
  • Comfortable in a modern web stack (TypeScript / React / Node or Python / Postgres / AWS or GCP).
  • Excellent written English.
  • Based in Austin, TX.
Nice to Have
  • At least one shipped LLM-powered project, school project, hackathon, or side project, with some kind of eval story.
  • Agent frameworks (LangGraph, CrewAI, Mastra, custom), vector search / RAG, evals (Braintrust, LangSmith, custom), prompt caching, MCP servers, structured output / tool-use, or voice agents.
  • Public GitHub or a personal AI project we can actually try.
  • A personal project you built because you wanted to.
  • Background in education, edtech, or sports.