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Soccer Data Analytics Jobs (NOW HIRING)

Swish Analytics

Soccer Data Scientist

San Francisco, CA · On-site +1

$130K/yr

Company Description Swish Analytics is a sports analytics, betting and fantasy startup building the ... Swish Analytics is looking for a Soccer Data Scientists to join our ever-growing team! Data Science ...

Swish Analytics

Soccer Data Scientist

San Francisco, CA · On-site

$130K/yr

Company Description Swish Analytics is a sports analytics, betting and fantasy startup building the ... Swish Analytics is looking for a Soccer Data Scientists to join our ever-growing team! Data Science ...

Bay FC

Head of Data & Analytics

San Jose, CA · On-site

Bay FC is the first NWSL team in the Bay Area, co-founded by legends of women's soccer. The Head of Data & Analytics will lead the execution of the club's data strategy, overseeing the use and ...

Bay Football Club

Head of Data & Analytics

San Jose, CA · On-site

$140K/yr

Oversee the use, governance and quality of data across soccer operations and promote data-informed ... Ensure all analytical work reinforces the Club's football philosophy and supports the broader game ...

Sporting Kansas City

... Soccer. The First Team Performance Data Scientist will be tasked with connecting the first team sport science front end to SKC's centralized data analytics infrastructure. They will meet SKC ...

United Soccer League (USL)

$15.25 - $19/hr

Remote Overview of the United Soccer League (USL) The United Soccer League (USL) is the heartbeat ... The Participant will assume an integral role in the production of data analytics and distribution ...

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Soccer Data Analytics information

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$33K

$81.5K

$140K

How much do soccer data analytics jobs pay per year?

As of Aug 3, 2026, the average yearly pay for soccer data analytics in the United States is $81,518.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $96,500.00 per year, depending on experience, location, and employer.

What is a Soccer Data Analytics job?

A Soccer Data Analytics job involves analyzing data related to player performance, team tactics, and match statistics to derive insights that can improve decision-making. Analysts use data visualization, statistical models, and machine learning to assess player strengths, predict outcomes, and optimize strategies. They work with coaches, scouts, and front offices to provide data-driven recommendations for player recruitment, game tactics, and performance evaluation. Their role is crucial in modern soccer, where data helps gain a competitive edge.

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

To thrive in Soccer Data Analytics, a strong background in statistics, programming (such as Python or R), and a solid understanding of soccer tactics are generally required, often with a degree in data science, mathematics, or a related field. Familiarity with data visualization tools like Tableau, sports data platforms such as Opta, and certifications in analytics can further enhance your profile. Excellent communication, attention to detail, and the ability to work collaboratively with coaches and technical staff are valuable soft skills. These qualities are vital for extracting actionable insights that directly impact team performance and decision-making.

What does a typical day look like for someone working in Soccer Data Analytics?

A typical day in Soccer Data Analytics involves collecting and cleaning match and player data, performing statistical analyses, and creating visual reports to present findings to coaches and stakeholders. Analysts often work closely with coaching staff to tailor insights to current team strategies and may attend training sessions or matches to gain contextual understanding. Collaboration with other analysts, scouts, and performance departments is common, ensuring a shared approach to improving player performance and team tactics. The role balances independent analytical work with cross-functional teamwork, providing a dynamic and fast-paced work environment.

More about Soccer Data Analytics jobs
What cities are hiring for Soccer Data Analytics jobs? Cities with the most Soccer Data Analytics job openings:
What are the most commonly searched types of Soccer Data Analytics jobs? The most popular types of Soccer Data Analytics jobs are:
What states have the most Soccer Data Analytics jobs? States with the most job openings for Soccer Data Analytics jobs include:
What job categories do people searching Soccer Data Analytics jobs look for? The top searched job categories for Soccer Data Analytics jobs are:
Soccer Data Analytics jobs near you
Infographic showing various Soccer Data 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 $81,518 per year, or $39.2 per hour.

Soccer Data Scientist

Swish Analytics

San Francisco, CA • On-site, Remote

$130K/yr

Full-time

Re-posted 16 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
Swish Analytics is looking for a Soccer Data Scientists to join our ever-growing team! Data Science is at the core of our business, so this team has true ownership and impact over developing core components of Swish's data products. This position is remote from the USA.
Duties:
  • Ideate, develop and improve machine learning and statistical models that drive Swish's core algorithms for producing state-of-the-art sports betting products.
  • Develop contextualized feature sets using sports specific domain knowledge.
  • Contribute to all stages of model development, from creating proof-of-concepts and beta testing, to partnering with data engineering and product teams to deploy new models.
  • Strive to constantly improve model performance using insights from rigorous offline and online experimentation.
  • Analyze results and outputs to assess model performance and identify model weaknesses for directing development efforts.
  • Adhere to software engineering best practices and contribute to shared code repositories.
  • Document modeling work and present to stakeholders and other technical and non-technical partners.

Requirements:
  • Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area
  • Demonstrated experience developing models at production scale for Soccer, or sports betting for 2+ years
  • Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods
  • 5+ years of demonstrated experience developing and delivering effective machine learning and/or statistical models to serve business needs in sports or sports betting
  • Experience with relational SQL & Python
  • Experience with source control tools such as GitHub and related CI/CD processes
  • Experience working in AWS environments etc
  • Proven track record of strong leadership skills. Has shown ability to partner with teams in solving complex problems by taking a broad perspective to identify innovative solutions
  • Excellent communication skills to both technical and non-technical audiences

Base Salary: Starting at $130,000
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 Soccer Team Locations San Francisco, CA - Remote Remote status Fully Remote

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