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Nfl Data Analytics Jobs (NOW HIRING)

Swish Analytics

Data Scientist

San Francisco, CA · On-site +1

$150K/yr

Company Description Swish Analytics is a sports analytics, betting and fantasy startup building the ... Department Data Science Role NFL Team Locations San Francisco, CA - Remote Remote status Fully ...

AEG

Head of Analytics

Chicago, IL · On-site

$120K - $140K/yr

Based in downtown Chicago, Trajektory is an innovative data insights and valuation technology ... the NFL, NBA, MLB, NHL, NCAA, WNBA, AFL, and e-sports. Culture is a major priority, as both ...

Swish Analytics

Trading Analyst

San Francisco, CA · On-site +1

$65K/yr

... analytics data products. We believe that oddsmaking is a challenge rooted in engineering ... Passion and intimate knowledge of the NBA, NFL, MLB, NHL, and NCAA Basketball + Football * Strong ...

Swish Analytics

Trading Analyst

San Francisco, CA · Remote

$65K/yr

... analytics data products. We believe that oddsmaking is a challenge rooted in engineering ... Passion and intimate knowledge of the NBA, NFL, MLB, NHL, and NCAA Basketball + Football * Strong ...

Triwill Group

$150 - $200/hr

Proven track record leading complex data and analytics programs, including cloud data platforms ... The NFL expects to hire for this position near the middle of the range. Only in truly rare and ...

New

leeenterprises

Buffalo Bills Beat Reporter

Buffalo, NY · On-site

$23.25 - $31.50/hr

Monitor data analytics to understand what our readers want. * Be a strong storyteller who can report on the inner workings of the Bills organization and the rest of the NFL. Other requirements ...

leeenterprises

Buffalo Bills Beat Reporter

Buffalo, NY · On-site

$23.25 - $31.50/hr

Monitor data analytics to understand what our readers want. * Be a strong storyteller who can report on the inner workings of the Bills organization and the rest of the NFL. Other requirements ...

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NFL Data Analytics information

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How much do nfl data analytics jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for nfl data analytics in the United States is $59.24, according to ZipRecruiter salary data. Most workers in this role earn between $58.65 and $59.86 per hour, depending on experience, location, and employer.

What is an NFL Data Analytics?

An NFL Data Analytics job involves collecting, interpreting, and visualizing football-related data to support teams, coaches, and analysts in making informed decisions. Professionals in this role use statistical models and machine learning techniques to evaluate player performance, game strategies, and scouting insights. They work with large datasets, including player tracking data and in-game statistics, to optimize team performance, prevent injuries, and gain a competitive edge. These roles can be found within NFL teams, media companies, or technology firms specializing in sports analytics. Strong skills in programming, data analysis, and football knowledge are essential for success in this field.

What are the typical responsibilities of an NFL Data Analytics professional during the football season?

During the football season, NFL Data Analytics professionals are responsible for collecting and analyzing player and team performance data, preparing reports for coaches, and generating predictive models for upcoming games. They often collaborate with coaching staff and scouts to translate data insights into actionable game plans, while also monitoring player health and workload metrics. The role may also involve real-time analysis during games to support strategy adjustments. Being able to communicate complex analyses clearly to non-technical stakeholders is a frequent and critical task.

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

To thrive in NFL Data Analytics, you need strong skills in statistics, data modeling, programming (such as Python or R), and a relevant degree in mathematics, statistics, computer science, or a related field. Familiarity with data visualization tools, advanced analytics platforms, and sports-specific databases is highly valued, with certifications in data analytics being a plus. Excellent attention to detail, collaboration, and communication skills are essential for presenting insights to coaches and executives. These competencies ensure data-driven decision-making that directly impacts team performance and strategy.

Do NFL teams hire data analysts?

Yes, 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 skills in data management, programming, and sports analytics software, and may involve working closely with coaching staff and management.

How to become an NFL Data Analytics analyst?

To become an NFL Data Analytics analyst, you typically need a bachelor's degree in fields like statistics, data science, or sports management. Developing skills in programming languages such as Python or R, and proficiency with data visualization tools like Tableau, are also important. Gaining experience through internships or projects related to sports analytics can improve job prospects.
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NFL Data Analytics jobs near you
Infographic showing various Nfl Data Analytics job openings in the United States as of September 2026, with employment types broken down into 87% Full Time, 9% Part Time, and 4% Temporary. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $123,210 per year, or $59.2 per hour.

Data Scientist

San Francisco, CA • On-site, Remote

Swish Analytics
Spectator Sports • 1 - 10 employees
Learn more about Swish Analyticsexternal

$150K/yr

Full-time

Re-posted 21 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.
Job Description
You'll be joining a team that is working to develop the infrastructure for a system to optimize our simulation outputs based on a variety of external and internal signals. This role will work at the intersection of data science, trading, and data engineering to help develop and maintain trader automation algorithms that will react faster to signals as well as improve model accuracy. This position is remote from the USA or Canada.
Duties:
  • Develop infrastructure for trader automation and system performance tracking
  • Develop high-performance and low-latency products to react to external and internal signals
  • Analysis of live-streaming data and turning it into actionable decisions
  • Design and set up tests to detect unexpected changes to our models resulting from manual interactions.
  • Use extensive experience to build, test, debug, and deploy production-grade components
  • Ideate, develop, and improve machine learning and statistical models that drive Swish's core algorithms, growing into top-level simulation output modeling as we expand to new sports.
  • Develop contextualized feature sets that draw on sports-specific domain knowledge.
  • Contribute across all stages of model development - from proof-of-concept and beta testing to partnering with data engineering and product teams to deploy new models.
  • Constantly improve model performance using insights from rigorous experimentation.
  • Assess model performance, identify weaknesses, and use those findings to direct development efforts.
  • Document your work and present it clearly to technical and non-technical partners.

Requirements
  • Bachelor's in Data Science, Statistics, Computer Science, Applied Math, or a related technical field; Master's strongly preferred.
  • 4+ years developing and delivering effective machine learning and/or statistical models to serve real business needs in sports analytics or sports betting.
  • Experience in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, and Markov Chain Monte Carlo methods.
  • Excellent analytical and problem-solving ability, and a demonstrated drive to learn quickly in unfamiliar territory.
  • Experience with Python and relational SQL.
  • Strong foundation with source control (GitHub) and related CI/CD processes.
  • Strong foundation working in AWS environments.
  • Ideal candidates will have experience with Kafka, Docker, and Kubernetes
  • Ability to partner across teams on complex, ambiguous problems and communicate clearly with technical and non-technical audiences.

Base salary: Starting at $150,000 - 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 those 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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