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Remote Football Data Analytics Jobs (NOW HIRING)

Swish Analytics

Sports Data Analyst

San Francisco, CA · On-site +1

Company Description Swish Analytics is a sports analytics, betting and fantasy startup building the ... Deep knowledge of football, basketball or baseball; including roster compositions of professional ...

SumerSports LLC

Sr. Football Data Scientist

We are seeking a motivated and skilled Senior Data Scientist to join our analytics team. You will ... Remote working environment * A flexible, unlimited time off policy * Generous paid holiday schedule ...

Ursus, Inc.

Sr. Football Data Scientist

Responsibilities : • Build and implement analytical football models, providing valuable insights to enhance our football analytics offerings. Conduct comprehensive data analysis to extract ...

NuView Analytics

Data Analyst (Remote)

Denver, CO · Remote

$80K - $100K/yr

At NuView Analytics we help companies accelerate the time to insights from their data. We do this ... Salary: $80k100K + bonus + benefits Location: 100% remote for US-based candidates Responsibilities:

PFF

Senior Data Engineer

$120K - $160K/yr

About PFF PFF is a leading sports analytics company that transforms complex football data into ... Remote (United States)

NuView Analytics

Senior Data Analyst (Remote)

Denver, CO · Remote

$90K - $120K/yr

100% Remote Full-time Senior Analyst At NuView Analytics we help companies accelerate the time to ... We do this in three ways data analytics, data diligence, and fractional data science. Our clients ...

Parsons

Data Analytics Architect

Alexandria, VA · On-site +1

The Data Analytics Architect leads the design, integration, and governance of data systems that ... FAA Part 107 Remote Pilot Certification (required) Physical Requirements / Working Conditions ...

ICF

Manager, Data Analytics - Remote

Reston, VA · Remote

ICF is seeking an experienced Data Analytics Manager to lead enterprise data, analytics, governance ... This position is remote within the United States. Please note that ICF monitors employee work ...

NuView Analytics

Data Analyst

Denver, CO · Remote

Salary: $80k-100K + bonus + benefits Location: 100% remote for US-based candidates Responsibilities: * Candidate will complete data analytics and data science projects for clients * Candidate will ...

NuView Analytics

Senior Data Analyst

Denver, CO · Remote

Salary: $90k-120K + bonus + benefits Location: 100% remote for US-based candidates Responsibilities: * Candidate will complete data analytics and data science projects for clients * Candidate will be ...

EV Realty

Intern, Data Analytics

San Francisco, CA · On-site +1

The Role As a Data Analytics Intern you will help build and maintain various analytics tools and ... Independent workflow must be effectively harmonized with remote collaboration * Familiarity with ...

CAPTRUST

Data & Analytics Lead

$110K - $120K/yr

The CAPTRUST at Work is seeking a Data & Analytics Lead who will be responsible for managing how ... Remote HOW do we build a world class organization one brick at a time? We make it a priority to ...

Intermountain Health

A strategic leader overseeing data and analytics operations across various departments and regions ... Candidates outside of Utah may be considered, but we are are not currently hiring remote workers in ...

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Remote Football Data Analytics information

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$24

$54

$94

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

As of Jun 8, 2026, the average hourly pay for remote football data analytics in the United States is $54.75, according to ZipRecruiter salary data. Most workers in this role earn between $43.99 and $62.02 per hour, depending on experience, location, and employer.

How do remote football data analytics professionals typically collaborate with coaches and team analysts?

Remote football data analytics professionals often work closely with coaches and on-site analysts through regular virtual meetings, data-sharing platforms, and real-time communication tools. They are responsible for delivering insightful reports, visualizations, and actionable recommendations that inform game strategies and player development. Clear communication and a collaborative mindset are essential, as these professionals need to translate complex data into accessible insights while responding promptly to feedback and changing team needs.

What is the difference between Remote Football Data Analytics vs Remote Sports Data Analyst?

AspectRemote Football Data AnalyticsRemote Sports Data Analyst
CredentialsDegree in Data Science, Sports Management, or related field; knowledge of football statisticsDegree in Data Science, Sports Management, or related field; broad sports knowledge
Work EnvironmentRemote, focused on football data projectsRemote, covering multiple sports or general sports data analysis
Industry UsagePrimarily in football clubs, leagues, and football-focused mediaIn various sports organizations, media outlets, and analytics firms
Search & Comparison IntentSpecific to football data analysis rolesBroader sports data analysis roles

Remote Football Data Analytics focuses specifically on football-related data, requiring specialized football knowledge and analytics skills. In contrast, Remote Sports Data Analyst roles encompass multiple sports, demanding broader sports industry understanding. Both roles often share similar credentials and work environments but differ in their scope and industry focus.

What is a Remote Football Data Analyst?

A Remote Football Data Analyst is a professional who collects, processes, and interprets football-related data from a remote location, often using specialized software and statistical methods. They analyze match statistics, player performance data, and tactical trends to provide insights for teams, media, or betting companies. Their work helps improve team strategies, scouting, and fan engagement, all while working outside of a traditional office or stadium environment. This role requires strong analytical skills, a deep understanding of football, and proficiency in data analysis tools.

What are the key skills and qualifications needed to thrive as a Remote Football Data Analyst, and why are they important?

To thrive as a Remote Football Data Analyst, you need strong skills in statistical analysis, data interpretation, and a solid understanding of football tactics, typically supported by a degree in statistics, mathematics, or sports science. Proficiency with data analysis tools like Python, R, SQL, and sports analytics platforms such as Opta or Wyscout is highly valued. Excellent communication, attention to detail, and the ability to work independently are crucial soft skills for this remote role. These skills are important to deliver actionable insights that drive team performance and informed decision-making in a competitive sports environment.
More about Remote Football Data Analytics jobs
What cities are hiring for Remote Football Data Analytics jobs? Cities with the most Remote Football Data Analytics job openings:
What are the most commonly searched types of Football Data Analytics jobs? The most popular types of Football Data Analytics jobs are:
What states have the most Remote Football Data Analytics jobs? States with the most job openings for Remote Football Data Analytics jobs include:
What job categories do people searching Remote Football Data Analytics jobs look for? The top searched job categories for Remote Football Data Analytics jobs are:
Remote Football Data Analytics jobs near you
Infographic showing various Remote Football Data Analytics job openings in the United States as of May 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% Remote job distribution, with an average salary of $113,873 per year, or $54.7 per hour.
Sports Data Analyst

Sports Data Analyst

Swish Analytics

San Francisco, CA • On-site, Remote

Full-time

Posted 12 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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