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Football Data Science Jobs (NOW HIRING)

SumerSports LLC

Sr. Football Data Scientist

SumerSports is a leading football intelligence technology company that specializes in providing an ... Experience: 4+ years of experience in data science, preferably in a sports analytics environment ...

Swish Analytics

Sports Data Analyst

San Francisco, CA · On-site +1

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 ...

SumerSports LLC

Product Manager

... football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia. Our data-driven platform ...

SumerSports LLC

Sr. Product Manager

$129K - $170K/yr

... football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia. Our data-driven platform ...

SumerSports LLC

Data Engineer

$117K - $140K/yr

... football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia. Our data-driven platform ...

Bay Football Club

Head of Data & Analytics

San Jose, CA · On-site

$140K/yr

... science, performance analysis, or analytics roles within professional football or elite sports. * Hands-on background with player monitoring technologies. * Familiarity with football specific data ...

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Football Data Science information

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$18K

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How much do football data science jobs pay per year?

As of Jul 4, 2026, the average yearly pay for football data science in the United States is $105,382.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,000.00 and $154,000.00 per year, depending on experience, location, and employer.

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

To thrive in Football Data Science, a strong background in statistics, data analysis, and programming (often with a degree in mathematics, computer science, or a related field) is essential. Proficiency with technical tools such as Python, R, SQL, and specialized sports analytics software, as well as relevant certifications or experience with machine learning, is highly valued. Strong communication skills, teamwork, and the ability to present complex findings to non-technical stakeholders help practitioners excel. These abilities enable data scientists to deliver actionable insights for team performance, recruitment, and strategic planning, which are critical to success in this data-driven field.

What is a Football Data Science job?

A Football Data Science job involves analyzing football-related data to extract insights that can help teams, analysts, and decision-makers improve performance and strategy. This role typically includes working with player tracking data, match statistics, and scouting reports to create predictive models, visualizations, and performance metrics. Professionals in this field use programming languages like Python or R, along with machine learning and statistical techniques, to analyze large datasets. The insights gained can influence tactical decisions, player recruitment, injury prevention, and opposition analysis.

What are some typical daily tasks for someone working in Football Data Science?

A typical day in Football Data Science may involve gathering and cleaning match data, building statistical models to analyze player and team performance, and generating reports or dashboards for coaching staff and management. You might also work on developing predictive metrics, collaborating with scouts to analyze potential recruits, and communicating findings to various stakeholders. Regular meetings with analysts, coaches, and technical teams are common to ensure alignment on objectives and data-driven strategies. This role often balances independent analysis with collaborative teamwork, making it dynamic and closely tied to both match preparation and long-term club strategy.

More about Football Data Science jobs
What are the most commonly searched types of Football Data Science jobs? The most popular types of Football Data Science jobs are:
What states have the most Football Data Science jobs? States with the most job openings for Football Data Science jobs include:
What job categories do people searching Football Data Science jobs look for? The top searched job categories for Football Data Science jobs are:
Football Data Science jobs near you
Infographic showing various Football Data Science job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 96% Full Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $105,382 per year, or $50.7 per hour.

Sr. Football Data Scientist

SumerSports LLC

Remote

Full-time

Medical, Retirement

Posted 12 days ago

Job description

SumerSports is a leading football intelligence technology company that specializes in providing an innovative suite of products for football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia.
Our data-driven platform empowers teams with insights and tools to make informed decisions within salary cap constraints. The platform also serves the NCAA, offering insights around the transfer portal and more.
What sets us apart is our unique blend of big tech talent, data scientists, and former NFL personnel, who have a combined 600+ years of NFL experience. Our domain knowledge is augmented by AI and machine learning technologies to create a unique view into many aspects of Football.
We are seeking a motivated and skilled Senior Data Scientist to join our analytics team. You will be responsible for building, deploying, and refining a variety of football-focused analytical models, working with complex real-world datasets. You'll collaborate closely with other data scientists and engineers, ensuring our analytical products are accurate, robust, and impactful. The ideal candidate will demonstrate both strong technical skills and a proactive mindset, capable of independently taking projects from concept to deployment.
Responsibilities
  • Model Development and Analysis: Build and implement analytical football models, providing valuable insights to enhance our football analytics offerings. Conduct comprehensive data analysis to extract actionable insights.
  • Model Productionization: Ensure seamless deployment of machine learning and statistical models using Python, Databricks, and Spark. You will work on converting existing R models to Python as part of your initial responsibilities.
  • Large Dataset Management: Handle large datasets efficiently using Spark and Databricks, ensuring data integrity and performance optimization.
  • Collaboration: Work closely with other data scientists, analysts, and stakeholders to understand their needs and deliver high-quality analytical solutions.
  • Innovation: Identify and implement new tools, techniques, and best practices to enhance our data analytics capabilities.

Qualifications
Education: Advanced degree (Masters or PhD) in a quantitative discipline, or equivalent professional experience.
Experience: 4+ years of experience in data science, preferably in a sports analytics environment. (level commensurate with experience)
Technical Skills:
  • Proficiency in Python and experience with Databricks.
  • Strong programming skills in Python, including experience deploying models beyond exploratory notebooks.
  • Documented experience in football analytics, demonstrated through industry experience, public content, or
    significant independent projects. 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 Github repos.
  • Solid foundation in statistical modeling and machine learning methodologies.
  • Proven ability to independently identify and resolve data-related challenges in real-world datasets.
  • Effective communication skills, with experience explaining technical concepts clearly

Benefits
  • Competitive Salary and Bonus Plan
  • Comprehensive health insurance plan
  • Retirement savings plan (401k) with company match
  • Remote working environment
  • A flexible, unlimited time off policy
  • Generous paid holiday schedule - 13 in total including Monday after the Super Bowl

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