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Football Data Analytics Internship Jobs (NOW HIRING)

Swish Analytics

Sports Data Analyst

San Francisco, CA · On-site +1

Deep knowledge of a second sport including football, basketball, baseball, hockey or tennis * Exposure to the data science process and tech stack * Anomaly Detection Techniques Swish Analytics is an ...

SumerSports LLC

Sr. Football Data Scientist

Build and implement analytical football models, providing valuable insights to enhance our football analytics offerings. Conduct comprehensive data analysis to extract actionable insights. * Model ...

Bay Football Club

Head of Data & Analytics

San Jose, CA · On-site

$140K/yr

While our community is our foundation, our love of football is our reason for being. We have the ... Position Summary The Head of Data & Analytics will lead the execution and adoption of Bay FC's data ...

TrinityRail

Data Analytics Intern

Dallas, TX · On-site

Trinity Industry is looking for Data Analytics Interns for our office in Dallas, TX . This position will focus on building, deploying, and scaling agentic AI applications and automated workflows ...

Trinity Industries

Data Analytics Intern

Dallas, TX · On-site

Trinity Industry is looking for Data Analytics Interns for our office in Dallas, TX . This position will focus on building, deploying, and scaling agentic AI applications and automated workflows ...

ConnectPrep

Data Analyst Internship

Washington, DC · On-site +1

AI, data, and analytics work you will support * Work with AI tools and workflows to support data ... Prior internship or project experience in data analysis, business intelligence, or marketing ...

ConnectPrep

Data Analyst Internship

Washington, DC · On-site +1

AI, data, and analytics work you will support * Work with AI tools and workflows to support data ... Prior internship or project experience in data analysis, business intelligence, or marketing ...

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Football Data Analytics Internship information

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How much do football data analytics internship jobs pay per hour?

As of Jul 22, 2026, the average hourly pay for football data analytics internship in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

How much do NFL data analysts make?

NFL data analysts typically earn between $50,000 and $100,000 annually, depending on experience and location. Entry-level positions may start lower, while experienced analysts with advanced skills in data visualization and statistical software can earn higher salaries.

What is a Football Data Analytics Internship job?

A Football Data Analytics Internship is a temporary role where interns analyze football-related data to provide insights for teams, analysts, or organizations. Responsibilities may include data collection, statistical analysis, performance evaluation, and assisting with predictive modeling. Interns typically work with software like Python, R, Excel, and SQL to interpret data and present findings. This role helps interns gain practical experience in sports analytics, improving their technical and analytical skills.

What types of projects or daily tasks are typically assigned to Football Data Analytics Interns?

As a Football Data Analytics Intern, you can expect to work on tasks such as collecting and cleaning match data, conducting statistical analyses of player and team performance, and generating reports or visualizations for coaches and analysts. Interns often support ongoing research projects, contribute to scouting or tactical analyses, and may assist in developing predictive models. Collaboration with full-time analysts, coaches, and sometimes technical staff is common, providing valuable exposure to different areas of football operations. This variety of tasks helps interns develop both technical and applied skills relevant to a career in sports analytics.

What does a football analytics intern do?

A football analytics intern analyzes game data, player performance, and team statistics to provide insights that support coaching and strategic decisions. They often use data analysis tools and software, such as Excel or specialized sports analytics platforms, and may assist in preparing reports or visualizations for coaching staff and management.

What are the key skills and qualifications needed to thrive in the Football Data Analytics Internship position, and why are they important?

To thrive as a Football Data Analytics Intern, you need a solid understanding of statistics, data analysis, and football tactics, often demonstrated through coursework in data science, mathematics, or a related field. Experience with programming languages such as Python or R, familiarity with tools like Excel and Tableau, and knowledge of sports analytics software are commonly expected. Strong attention to detail, effective communication, and the ability to collaborate within a fast-paced team environment are highly valued soft skills. These abilities enable interns to extract actionable insights, clearly present findings, and contribute to data-driven decision-making within football organizations.

Do NFL teams hire data analysts?

NFL teams often hire data analysts to evaluate player performance, develop strategies, and improve decision-making using statistical tools and data analysis techniques. These roles typically require knowledge of sports analytics software, programming languages like Python or R, and a background in sports or data science. Data analysts in sports organizations contribute to competitive advantages through data-driven insights.

How to get into football data analytics?

To get into football data analytics, develop skills in data analysis, statistics, and programming languages like Python or R. Gain experience with sports data sources, learn to use analytics tools, and consider pursuing relevant degrees or certifications in sports management, data science, or related fields.
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Football Data Analytics Internship jobs near you
Infographic showing various Football Data Analytics Internship job openings in the United States as of July 2026, with employment types broken down into 95% Full Time, 3% Part Time, and 2% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.
Sports Data Analyst

Sports Data Analyst

Swish Analytics

San Francisco, CA • On-site, Remote

Full-time

Posted 26 days ago

Job description

Company Description
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.
Duties:
  • Work closely with Data Scientists and Engineers to diagnose and treat data pipeline integrity issues
  • Detect data inaccuracies such as missing, out of range or otherwise incorrect on-field data
  • Source origins of data inaccuracies through data pipeline dependencies and python code base
  • Define data validation tests to flag future game errors
  • Research accurate roster active statuses, primary positions and game participation
  • Validate data changes after logic updates
  • Production model feature deep dives to explain project market lines
  • Clearly document findings
  • Develop intimate familiarity with existing databases and construct metadata references
  • With guidance, support lead Data Scientists in feature development and model analysis

Requirements:
  • Bachelor's Degree in Computer Science, Data Science or similar major
  • Minimum of 1 year of experience in football data analysis
  • Deep knowledge of football, basketball or baseball; including roster compositions of professional and college teams, general gameplay strategies, and typical in-game scenarios
  • Data Extraction, Wrangling and Analysis in Python
  • Strong SQL querying skills
  • Attention to detail

Preferred:
  • Strong Python data management programming skills
  • Data Visualization experience with a user application like Streamlit
  • Deep knowledge of a second sport including football, basketball, baseball, hockey or tennis
  • Exposure to the data science process and tech stack
  • Anomaly Detection Techniques

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer's discretion, this position may require successful completion of background and reference checks.
Department Data Science Role NFL Team Locations San Francisco, CA - Remote Remote status Fully Remote

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