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Freelance 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 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 ...

Procter & Gamble

Data Analyst

Mason, OH · On-site +1

A Data Analyst collects, cleans, and analyzes data to identify trends and patterns that inform ... Successful candidates for freelancer opportunities will not be considered employees of The Procter ...

Solomon Page

Data Analyst

Austin, TX · On-site

$40 - $50/hr

Required Qualifications: * 3+ years of experience in Data Analytics, Business Intelligence, or a ... freelancers - which sets us apart in the industries we serve. About Solomon Page Founded in 1990 ...

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How much do freelance soccer data analytics jobs pay per hour?

As of Jul 17, 2026, the average hourly pay for freelance soccer data analytics in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

What is freelance soccer data analytics?

Freelance soccer data analytics involves independently analyzing soccer-related data to provide insights for teams, coaches, media, or betting companies. Freelancers use statistics, performance metrics, and advanced software to evaluate player performance, team strategies, and match outcomes. They often work on a project-by-project basis, delivering reports, visualizations, or actionable recommendations. This role requires strong analytical skills, a deep understanding of soccer, and proficiency with data analysis tools. Freelance soccer data analysts may work remotely with clients worldwide.

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

To thrive as a Freelance Soccer Data Analyst, you need strong analytical skills, deep knowledge of soccer, and proficiency in statistics, often backed by a degree in mathematics, statistics, or a related field. Expertise in technical tools like Python, R, Excel, and data visualization platforms, as well as familiarity with sports analytics software such as Wyscout or Opta, is highly valuable. Excellent communication, critical thinking, and problem-solving abilities set standout analysts apart when interpreting data and presenting actionable insights to clients. These skills ensure accurate, impactful analysis that supports performance improvement and informed decision-making in a competitive sports environment.

What is the difference between Freelance Soccer Data Analytics vs Soccer Data Analyst?

AspectFreelance Soccer Data AnalyticsSoccer Data Analyst
CredentialsSelf-taught or certifications in data analysis, sports analytics, or related fieldsBachelor's or master's in data science, sports management, or related areas
Work EnvironmentRemote, project-based, independentEmployed by clubs, agencies, or organizations, often in-office or hybrid
Employer & Industry UsageFreelance clients, sports startups, consulting projectsProfessional sports teams, sports organizations, analytics firms

Freelance Soccer Data Analytics involves independent, project-based work often remotely, focusing on specific client needs. In contrast, a Soccer Data Analyst is typically employed full-time by organizations, working within a team environment. Both roles require strong data analysis skills, but the freelance role offers more flexibility and varied projects, while the analyst role provides stability and organizational integration.

How do freelance soccer data analysts typically collaborate with clubs or clients, and what tools are most commonly used in remote work settings?

Freelance soccer data analysts often work remotely and communicate with clubs, scouts, or agencies via video calls, emails, and collaborative platforms like Slack or Microsoft Teams. They typically share their analyses using data visualization tools such as Tableau or Power BI, and manage data using Python, R, or Excel. Regular feedback and updates are common, and successful freelancers are proactive in clarifying requirements and delivering actionable insights. Building strong client relationships and being responsive to changing needs are key to thriving in this role.
More about Freelance Soccer Data Analytics jobs
What cities are hiring for Freelance Soccer Data Analytics jobs? Cities with the most Freelance 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:
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What job categories do people searching Freelance Soccer Data Analytics jobs look for? The top searched job categories for Freelance Soccer Data Analytics jobs are:
Freelance Soccer Data Analytics jobs near you
Infographic showing various Freelance Soccer Data Analytics job openings in the United States as of July 2026, with employment types broken down into 1% Internship, 94% Full Time, 3% Part Time, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $99,230 per year, or $47.7 per hour.
Soccer Data Scientist

Soccer Data Scientist

Swish Analytics

San Francisco, CA • On-site, Remote

$130K/yr

Full-time

Re-posted 29 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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