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Internship Nfl Data Analyst Jobs in Colorado (NOW HIRING)

$22 - $24/hr

... or Data Analyst for Siemens. What is the FLDP Internship: The Finance Internship is a 12-week ... summer internship program that allows the opportunity to experience the day-to-day functions of a ...

$22 - $24/hr

... or Data Analyst for Siemens. What is the FLDP Internship: The Finance Internship is a 12-week ... summer internship program that allows the opportunity to experience the day-to-day functions of a ...

$22 - $24/hr

... or Data Analyst for Siemens. What is the FLDP Internship: The Finance Internship is a 12-week ... summer internship program that allows the opportunity to experience the day-to-day functions of a ...

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Internship Nfl Data Analyst information

What does an NFL data analyst intern do?

An NFL Data Analyst intern assists with collecting, cleaning, and analyzing football-related data to help teams and organizations make informed decisions. Their responsibilities often include working with player statistics, game data, and performance metrics using various tools and programming languages such as Excel, Python, or R. Interns may also help prepare reports, visualizations, and presentations for coaches, scouts, or executives. This role provides hands-on experience in sports analytics and a valuable introduction to data-driven decision-making in the NFL.

What are the key skills and qualifications needed to thrive as an NFL data analyst intern?

To thrive as an Internship NFL Data Analyst, you need a solid background in statistics, data analysis, and familiarity with football analytics, typically supported by coursework or a degree in statistics, mathematics, or a related field. Proficiency with data analysis tools such as Python, R, SQL, and visualization platforms like Tableau, as well as experience with sports data systems, is often required. Strong attention to detail, critical thinking, and effective communication skills help you interpret data and convey insights to both technical and non-technical stakeholders. These skills ensure accurate analysis, impactful reporting, and valuable contributions to team performance decisions.

What types of projects and data sets do NFL data analyst interns typically work with?

As an NFL Data Analyst intern, you'll often work with a variety of data sets, including player performance statistics, game footage analytics, injury reports, and scouting data. Typical projects may involve cleaning and visualizing large data sets, building predictive models, or generating reports to help coaches and front office staff make informed decisions about game strategy or player acquisitions. This hands-on work directly supports the analytics team and can have a real impact on how the organization approaches both short-term tactics and long-term planning.

What is the difference between Internship Nfl Data Analyst vs NFL Data Analyst?

AspectInternship NFL Data AnalystNFL Data Analyst
Required CredentialsEnrolled in or recent graduate of relevant degree programBachelor's or higher in data science, statistics, or related field
Work EnvironmentInternship setting, supervised, entry-level tasksFull-time, professional environment, independent analysis
Employer & Industry UsageSports teams, media, or analytics firms during internshipTeam organizations, media outlets, or analytics companies

The main difference is that an Internship NFL Data Analyst is a temporary, entry-level position for students or recent graduates gaining experience, while an NFL Data Analyst is a full-time professional role requiring more experience and responsibility in analyzing NFL data.

Do NFL teams hire internship NFL data analysts?

NFL teams do offer internship opportunities for data analysts, including roles focused on sports statistics, performance analysis, and data management. These internships typically require relevant skills in data analysis tools, programming, and sports knowledge, and are often available during the off-season or summer periods. Interested candidates should check team websites or sports industry job boards for specific openings and application details.

How much do NFL data analysts make?

NFL data analysts typically earn between $50,000 and $100,000 annually, depending on experience, education, and the level of responsibility. Entry-level analysts may start at lower salaries, while experienced professionals with advanced skills in data analysis tools and sports analytics can earn higher compensation. Salaries can also vary based on the organization and location.

How to get an internship in the NFL?

To secure an internship as an NFL data analyst, candidates should have strong analytical skills, proficiency in data tools like Excel, SQL, or Python, and a background in sports management, statistics, or related fields. Applying through official NFL internship programs or team-specific opportunities, and demonstrating relevant experience or projects, can improve chances of selection.

What cities in Colorado are hiring for Internship Nfl Data Analyst jobs?

Cities in Colorado with the most Internship Nfl Data Analyst job openings:

Infographic showing various Internship Nfl Data Analyst job openings in Colorado as of August 2026, with employment types broken down into 23% Internship, 50% Full Time, and 27% Part Time. Highlights an 89% In-person, and 11% Remote job distribution.

Operations Data Analyst

Fanatics Betting & Gaming

Denver, CO โ€ข On-site

Full-time

Re-posted 11 days ago


Job description

About the Team

Launched in 2021, Fanatics Betting and Gaming is the online and retail sports betting subsidiary of Fanatics, a global digital sports platform. The Fanatics Sportsbook is available to 95% of the addressable online sports bettor market in the U.S. Fanatics Casino is currently available online in Michigan, New Jersey, Pennsylvania and West Virginia. Fanatics Betting and Gaming operates twenty-two retail sports betting locations, including the only sportsbook inside an NFL stadium at Northwest Stadium. Fanatics Betting and Gaming is headquartered in New York with offices in Denver, Leeds and Dublin.

Overview

As an Operations Data Analyst at Fanatics Betting & Gaming, you are on the front lines of how the Operations Department understands its own performance. You sit within the Analytics & AI Enablement team and own the data pipelines, reporting, and analytical work that CX, Fraud, Payments, WFM, and VIP leaders rely on to make decisions every day.

This is not a passive reporting role. You are expected to take ownership across multiple operational areas, building and maintaining the data layer, surfacing insights, and flagging risks before they become crises. You work closely within the Strategy & Analytics team to ensure our data is accurate, scalable, and directly connected to Ops top-line goals.

We are actively building toward an AI-first way of operating, and this role is part of that. The ideal candidate is technically sharp, relentlessly detail-oriented, and genuinely curious, both about what the data is saying and about how AI can change the way we find and act on answers. You are comfortable moving fast, owning ambiguous problems, and holding yourself to a high bar without being told to.

Responsibilities

Analytical Work & Insights

  • Respond to high-priority analytical requests from Ops leaders - turning raw data into clear, actionable insights on a tight timeline.
  • Proactively surface trends, anomalies, and risks from the data without waiting to be asked.
  • Support scenario analysis and impact sizing for product initiatives, operational changes, and staffing decisions.
  • Own the development and maintenance of dashboards and reports that give operational leaders clear visibility into performance across CX, Fraud, Payments, WFM, and VIP.
  • Ensure all reporting reflects up-to-date data, clearly defined KPIs, and documented assumptions.
  • Present findings and data narratives directly to operational stakeholders - translating complexity into clear recommendations they can act on.

Data Infrastructure & Pipelines

  • Build, maintain, and improve data pipelines that feed Ops reporting and dashboards - ensuring consistent, accurate, and well-documented data flows.
  • Partner with Data Engineering on DBT development, data store buildout, and pipeline reliability.
  • Proactively identify and resolve data quality issues; escalate blockers that require cross-functional resolution.
  • Deprecate manual, one-off data pulls and replace with automated, always-on solutions.
  • Build alerting infrastructure on critical Ops metrics to catch issues early and reduce reactive firefighting.

AI Enablement & Innovation

  • Support the AI agent roadmap by contributing data, analytical rigor, and validated data foundations before an agent moves to build.
  • Track and report on AI agent performance post-deployment - measuring impact against top-line Ops goals.
  • Actively look for opportunities to apply AI to your own workflow - whether that's speeding up analysis, improving accuracy, or eliminating manual work.
  • Bring a point of view on where AI can and can't be trusted, and flag where human judgment needs to stay in the loop.
Required Qualifications
  • 2+ years of experience in an analytical role - business intelligence, data analytics, strategic operations, or a related field.
  • Strong hands-on SQL experience; ability to write, QA, and optimize complex queries independently.
  • Experience supporting AI/ML workflows, agent builds, or automation initiatives in an analytical capacity.
  • Experience building and maintaining dashboards in Sigma, Tableau, or a comparable data visualization tool.
  • Familiarity with DBT or similar data transformation frameworks.
  • High attention to detail - you catch data quality issues before they surface in leadership reporting.
  • Strong communication skills; able to translate analytical findings into plain language for operational stakeholders.
  • Comfortable operating in fast-paced, ambiguous environments with shifting priorities.
Preferred Qualifications
  • Familiarity with operational KPIs across customer support, fraud, payments, or workforce management.
  • Experience with Python or similar scripting languages for data manipulation and automation.
  • Experience in gaming, fintech, sports, or other operationally intensive, high-volume environments.
  • Bachelor's degree in Analytics, Computer Science, Statistics, Economics, or a related field.

Depending on the role, your interview and onboarding experience may include in-person components, such as onsite interviews or Launching into Better: LIVE-a multi-day cultural immersion in New York City for full-time, non-seasonal hires. These sessions are designed to build connection and bring our culture to life, though specific travel and participation requirements will be confirmed based on your role and location. Your recruiter will provide clear guidance at each stage of the process.

For information about our benefits, please visitย https://benefitsatfanatics.com/