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Sports Data Analyst Jobs in Colorado (NOW HIRING)

... Sports and Casino business units, serving as a key technical contributor to driving total commercial performance. * Collaborate with Data Scientists and Analysts to implement and refine scalable ...

Strategy & Analytics Analyst

Denver, CO · On-site

$57K - $85K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Data Analytics & Reporting: Design and execute complex analyses and reporting using tools such as ... Thrives in a feedback-rich environment, energized by the "sport" of deal work, with a natural ...

CRM Manager, Sports

Denver, CO · On-site

$105K - $130K/yr

As a CRM Manager, Sports you will develop the promotional strategy & lead in building customer ... Commercially minded, data literate with strong analytical skills, and comfortable in using raw data ...

As a CRM Manager, Sports you will develop the promotional strategy & lead in building customer ... Commercially minded, data literate with strong analytical skills, and comfortable in using raw data ...

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Sports Data Analyst information

See Colorado salary details

$35.8K

$86.9K

$143K

How much do sports data analyst jobs pay per year?

As of Aug 12, 2026, the average yearly pay for sports data analyst in Colorado is $86,898.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,700.00 and $102,000.00 per year, depending on experience, location, and employer.

How much do sports data analysts get paid?

Sports data analysts typically earn between $50,000 and $80,000 annually, with entry-level positions starting around $40,000 and experienced professionals earning over $100,000. Salaries vary based on experience, location, and the level of technical skills such as data modeling and statistical analysis.

What are the key skills and qualifications needed to thrive as a sports data analyst, and why are they important?

To thrive as a Sports Data Analyst, you need strong statistical analysis skills, a solid understanding of sports, and a relevant degree in mathematics, statistics, or data science. Proficiency in data analytics tools such as SQL, Python, R, and specialized sports analytics software is typically required. Attention to detail, critical thinking, and effective communication help analysts interpret data accurately and present insights clearly to coaches and management. These skills are crucial for transforming raw data into actionable strategies that enhance team performance and decision-making.

What is the difference between Sports Data Analyst vs Sports Statistician?

AspectSports Data AnalystSports Statistician
Required CredentialsBachelor's in Sports Management, Data Science, or related fields; proficiency in data analysis toolsBachelor's or Master's in Statistics, Mathematics, or related fields; strong statistical background
Work EnvironmentSports teams, analytics firms, media companiesResearch institutions, sports organizations, consulting firms
Employer & Industry UsageUsed for performance analysis, game strategy, and fan engagementUsed for statistical modeling, historical data analysis, and research

While both roles involve working with sports data, Sports Data Analysts focus on interpreting data for performance insights and strategic decisions, often using modern analytics tools. Sports Statisticians primarily handle statistical modeling and historical data analysis, emphasizing research and accuracy. Both roles are essential in the sports industry but serve different functions based on their focus and skill sets.

How do you become a sports data analyst?

To become a sports data analyst, typically a bachelor's degree in statistics, data science, sports management, or a related field is required. Developing skills in data analysis tools like Excel, SQL, and programming languages such as Python or R, along with knowledge of sports metrics and statistics, is essential. Gaining experience through internships or entry-level roles can also help build expertise in analyzing sports performance data.

What is a sports data analyst?

A sports data analyst is a professional who collects, analyzes, and interprets sports-related data to provide insights on team performance, player statistics, and game strategies. They often use statistical software, data visualization tools, and have knowledge of sports analytics methodologies to support decision-making in teams or organizations.

How do sports data analysts typically collaborate with coaches and athletes to impact team performance?

Sports Data Analysts work closely with coaches and athletes by translating complex data into actionable insights, such as identifying player strengths, weaknesses, and trends that can influence game strategies. Analysts often attend team meetings, review performance footage, and present their findings in clear, visual formats to ensure that coaching staff and athletes can easily apply the information. This collaborative approach helps teams make data-driven decisions on player selection, training focus, and in-game tactics, ultimately aiming to enhance overall team performance.

Can a sports data analyst work in sports?

Yes, sports data analysts often work directly within sports organizations, teams, or leagues to analyze player performance, game statistics, and team strategies. They use tools like statistical software and data visualization to support decision-making and improve team performance.
What are the most commonly searched types of Sports Data Analyst jobs in Colorado? The most popular types of Sports Data Analyst jobs in Colorado are:
What are popular job titles related to Sports Data Analyst jobs in Colorado? For Sports Data Analyst jobs in Colorado, the most frequently searched job titles are:
What cities in Colorado are hiring for Sports Data Analyst jobs? Cities in Colorado with the most Sports Data Analyst job openings:
Infographic showing various Sports Data Analyst job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $86,898 per year, or $41.8 per hour.

Full-time

Re-posted 25 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 visit https://benefitsatfanatics.com/