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Sport Analytics Jobs (NOW HIRING)

Swish Analytics

Tennis Data Scientist

San Francisco, CA · On-site +1

$135K - $190K/yr

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 ...

Swish Analytics

NFL Data Scientist

San Francisco, CA

$140K/yr

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 ...

Swish Analytics

NFL Data Scientist

San Francisco, CA · On-site +1

$140K/yr

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 ...

Swish Analytics

Tennis Data Scientist

San Francisco, CA · On-site

$135K - $190K/yr

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 ...

Swish Analytics

Rust Engineer

San Francisco, CA · On-site

$170K/yr

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 ...

Swish Analytics

Rust Engineer

San Francisco, CA · On-site +1

$170K/yr

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 ...

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Sport Analytics information

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$64.5K

$125.3K

$179K

How much do sport analytics jobs pay per year?

As of May 30, 2026, the average yearly pay for sport 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 are the key skills and qualifications needed to thrive as a Sports Analyst, and why are they important?

To thrive as a Sports Analyst, you need strong statistical analysis, data interpretation, and a solid understanding of sports concepts, often supported by a degree in statistics, mathematics, or sports management. Familiarity with analytics tools like R, Python, SQL, and sports-specific software is typically required, as are certifications in data analytics. Critical thinking, effective communication, and attention to detail are standout soft skills in this role. These skills are vital for turning complex data into actionable insights that drive team performance and strategic decision-making.

What are some common challenges faced by professionals working in sport analytics, and how can they be addressed?

Professionals in sport analytics often face challenges such as integrating data from multiple sources, ensuring data accuracy, and effectively communicating insights to coaches and athletes. Navigating large datasets and translating technical findings into actionable strategies for non-technical team members requires strong collaboration and communication skills. Staying updated with evolving technologies and analytical methods is also crucial. Addressing these challenges typically involves ongoing professional development, adopting robust data management practices, and fostering strong relationships with other departments within the organization.

What is sport analytics?

Sport analytics is the process of collecting, analyzing, and interpreting data related to sports performance, strategies, and outcomes. It involves using statistical and mathematical methods to gain insights that can help teams, coaches, and athletes make informed decisions. Sport analytics can be applied to player performance, injury prevention, game tactics, and business aspects such as fan engagement. The field is growing rapidly with advancements in technology and data collection tools, making it an essential part of modern sports organizations.

Do sports analysts make good money?

Sports analysts can earn a wide range of salaries depending on experience, employer, and level of expertise. Entry-level positions may pay modestly, while experienced analysts working for major sports organizations or media outlets can earn six-figure incomes. Skills in data analysis, statistics, and familiarity with tools like Excel or sports databases are important for higher earning potential.

What is the difference between Sport Analytics vs Sports Data Analyst?

AspectSport AnalyticsSports Data Analyst
Required CredentialsDegree in Sports Management, Statistics, or related fields; often certifications in data analysisSimilar credentials; degrees in Statistics, Data Science, or related fields; certifications in data tools
Work EnvironmentSports teams, leagues, or organizations; focus on performance and strategySports organizations, media, or analytics firms; focus on data interpretation and reporting
Employer & Industry UsageUsed by sports teams, leagues, and analytics companies for strategic decisionsEmployed by sports organizations, media outlets, and analytics firms for insights and reporting

Sport Analytics and Sports Data Analyst roles share similar educational backgrounds and work environments, often overlapping in skills and employer types. However, Sport Analytics typically emphasizes strategic decision-making and performance analysis, while Sports Data Analysts focus more on data collection, interpretation, and reporting. Both roles are vital in the sports industry for enhancing team performance and audience engagement.

More about Sport Analytics jobs
What cities are hiring for Sport Analytics jobs? Cities with the most Sport Analytics job openings:
What states have the most Sport Analytics jobs? States with the most job openings for Sport Analytics jobs include:
What job categories do people searching Sport Analytics jobs look for? The top searched job categories for Sport Analytics jobs are:
Sport Analytics jobs near you
Infographic showing various Sport Analytics job openings in the United States as of May 2026, with employment types broken down into 68% Full Time, 30% Part Time, 1% Temporary, and 1% Contract. Highlights an 53% Physical, 13% Hybrid, and 34% Remote job distribution, with an average salary of $125,326 per year, or $60.3 per hour.
Tennis Data Scientist

Tennis Data Scientist

Swish Analytics

San Francisco, CA • On-site, Remote

$135K - $190K/yr

Full-time

Posted 10 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 Tennis 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 Tennis 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: $135,000 - $190,000
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 Tennis Team Locations San Francisco, CA - Remote Remote status Fully Remote

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