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Nfl Analytics Jobs (NOW HIRING)

Swish Analytics

Trading Analyst

San Francisco, CA · On-site +1

$80K/yr

Company Overview Swish Analytics is a sports analytics, betting and fantasy startup building the ... Passion and intimate knowledge of the NBA, NFL, MLB, NHL, and NCAA Basketball + Football * Strong ...

Swish Analytics

Trading Analyst

San Francisco, CA

Company Overview Swish Analytics is a sports analytics, betting, and fantasy startup building the ... Deep domain knowledge across high-turnover sporting verticals such as NBA, NFL, and Soccer

Swish Analytics

Trading Analyst

San Francisco, CA · On-site +1

Company Overview Swish Analytics is a sports analytics, betting, and fantasy startup building the ... Deep domain knowledge across high-turnover sporting verticals such as NBA, NFL, and Soccer

SumerSports LLC

Sr. Football Data Scientist

Examples would include working for an NFL or NCAA analytics department, working for a third party analytics provider, achievement in events such as the Big Data Bowl, or original football analytics ...

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NFL Analytics information

See salary details

$64.5K

$125.3K

$179K

How much do nfl analytics jobs pay per year?

As of Jul 24, 2026, the average yearly pay for nfl analytics in the United States is $125,326.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,000.00 and $149,000.00 per year, depending on experience, location, and employer.

What is NFL analytics?

NFL analytics refers to the use of data analysis, statistics, and advanced mathematical models to evaluate player performance, team strategies, and game outcomes in the National Football League (NFL). Analysts collect and interpret data from games, practices, and player tracking systems to provide insights that help teams make better decisions on player acquisitions, play calling, and in-game tactics. The field has grown significantly in recent years, influencing everything from draft strategies to in-game decision-making. NFL analytics professionals often work closely with coaches, scouts, and front office staff to translate complex data into actionable information.

What are some common challenges NFL analytics professionals face when integrating data insights with coaching decisions?

NFL analytics professionals often encounter challenges when ensuring that their data-driven recommendations are effectively communicated and adopted by coaches and players. Translating complex statistical models into actionable strategies requires strong collaboration skills and an understanding of football operations. Additionally, balancing traditional scouting insights with advanced metrics can be challenging, as some stakeholders may be skeptical of analytics-based decisions. Overcoming these hurdles typically involves building trust, tailoring presentations to different audiences, and demonstrating the real-world impact of analytics on performance and strategy.

What is the difference between Nfl Analytics vs Football Data Analyst?

AspectNfl AnalyticsFootball Data Analyst
Required CredentialsDegree in Sports Analytics, Statistics, or related field; knowledge of NFL dataDegree in Sports Science, Data Analysis, or related; familiarity with football metrics
Work EnvironmentSports teams, analytics firms, media outlets focused on NFLFootball teams, sports agencies, media, or consulting firms
Industry UsageSpecialized in NFL-specific data and insightsBroader football industry, including college and other leagues

While both roles involve analyzing football data, Nfl Analytics focuses specifically on NFL data and insights, often with a deeper specialization in NFL metrics. Football Data Analysts may work across various levels of football, including college and other leagues, with a broader scope. Both roles require strong analytical skills and familiarity with football statistics, but Nfl Analytics is more tailored to NFL-specific data and industry applications.

What are the key skills and qualifications needed to thrive as an NFL Analytics professional, and why are they important?

To thrive in NFL Analytics, you need strong quantitative analysis skills, proficiency in statistics, and a background in mathematics, data science, or a related field. Familiarity with programming languages like Python or R, experience with data visualization tools, and knowledge of football-specific analytics platforms are typically required. Exceptional problem-solving, communication, and teamwork skills help translate complex data into actionable insights for coaches and executives. These skills are vital for driving data-informed decisions that can improve team performance and competitive strategy.
More about NFL Analytics jobs
What cities are hiring for Nfl Analytics jobs? Cities with the most Nfl Analytics job openings:
What states have the most Nfl Analytics jobs? States with the most job openings for Nfl Analytics jobs include:
What job categories do people searching Nfl Analytics jobs look for? The top searched job categories for Nfl Analytics jobs are:
NFL Analytics jobs near you
Infographic showing various Nfl Analytics 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 $125,326 per year, or $60.3 per hour.
Trading Analyst

Trading Analyst

Swish Analytics

San Francisco, CA • On-site, Remote

$80K/yr

Full-time

Posted 27 days ago

Job description

Company Overview
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.
Job Description - This position is 100% Remote
Duties:
  • Manage client risk, ensuring the highest margins on Swish products through +EV decisions
  • Manage and oversee depth chart accuracy, making time-sensitive adjustments in both prematch & in-play settings
  • Strategically research & track verified news sources, being the first to uncover important news and understand the overall impact on betting markets
  • Independently analyze betting trends in a scientific process, turning data into quantifiable trading actions

Requirements:
  • Minimum of 3 years of in-play experience at a sportsbook
  • Deep understanding of sports betting and odds origination
  • Passion and intimate knowledge of the NBA, NFL, MLB, NHL, and NCAA Basketball + Football
  • Strong mathematical, statistical, and/or analytical skills - ability to understand and calculate + convert odds on the fly
  • Results driven work ethic - focused on improving process, results and profitability
  • Availability to work flexible schedules, including nights, weekends and/or holidays

Preferred:
  • Bachelor's Degree in a STEM discipline
  • An understanding of relational database systems (MySQL)
  • Experience working with cross functional teams (Data Science teams a plus)

Salary: $80,000 - DOE
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 Trading Operations Locations San Francisco, CA - Remote Remote status Fully Remote

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