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Professional Sports Analytics Jobs (NOW HIRING)

Company Description Swish Analytics is a sports analytics, betting and fantasy startup building the ... Deep knowledge of football, basketball or baseball; including roster compositions of professional ...

Company Description Swish Analytics is a sports analytics, betting and fantasy startup building the ... Deep knowledge of football, basketball or baseball; including roster compositions of professional ...

Company Description Swish Analytics is a sports analytics, betting and fantasy startup building the ... Deep knowledge of football, basketball or baseball; including roster compositions of professional ...

Rust Engineer

San Francisco, CA · On-site +1

$170K/yr

Company Description Swish Analytics is a sports analytics, betting and fantasy startup building the ... Deep knowledge of football, basketball or baseball; including roster compositions of professional ...

Junior Sports Trader

New York, NY · On-site

$60K - $90K/yr

... professional and college sports, with a strong understanding of how these markets behave before, during, and after live events * Partner closely with quantitative analysts and trading engineers to ...

Interest in daily fantasy sports, prediction markets, or sports analytics. What makes you stand out ... Networking and collaboration with fellow interns and industry professionals * Social events with ...

Undergraduate degree required * 3-5 years of experience in sports media, sports analytics or ... Strong interest in collegiate and professional sports Responsibilities: * Identify, investigate ...

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Professional Sports Analytics information

See salary details

$64.5K

$125.3K

$179K

How much do professional sports analytics jobs pay per year?

As of Jun 9, 2026, the average yearly pay for professional sports 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 some common challenges faced by professionals working in sports analytics, and how can they be addressed?

Professionals in sports analytics often face the challenge of communicating complex data insights to coaches, athletes, and executives who may not have a technical background. Balancing statistical rigor with actionable recommendations is crucial. Additionally, working with incomplete or noisy data can make it difficult to produce reliable analyses. Building strong collaborative relationships with team staff and continually improving data collection processes can help address these challenges and increase the impact of analytics within the organization.

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

AspectProfessional Sports AnalyticsSports Data Analyst
Required CredentialsDegree in sports management, statistics, or related fields; knowledge of sports analytics toolsDegree in statistics, data science, or related fields; proficiency in data analysis software
Work EnvironmentSports teams, leagues, or sports analytics firms; often on-site at sporting eventsSports organizations, media companies, or consulting firms; primarily office-based
Industry UsageUsed for strategic decision-making, player evaluation, and game analysisFocuses on data collection, analysis, and reporting to support sports performance and business decisions

While both roles involve analyzing sports data, Professional Sports Analytics typically emphasizes strategic insights directly impacting team performance and player evaluation, often within sports organizations. Sports Data Analysts may have a broader focus on data collection and reporting across various sports-related industries. Understanding these distinctions helps clarify career paths and employer expectations in the sports analytics field.

What are professional sports analysts?

Professional sports analysts are experts who use statistical methods, data modeling, and technology to evaluate and interpret data related to athletic performance, team strategy, and game outcomes. They work for sports teams, media outlets, or independent firms, providing insights that help coaches, athletes, and executives make informed decisions. Their work involves collecting and analyzing large datasets, creating predictive models, and communicating findings to non-technical stakeholders to improve team performance and competitive advantage.

What are the key skills and qualifications needed to thrive as a Professional Sports Analyst, and why are they important?

To thrive as a Professional Sports Analyst, you need strong statistical analysis skills, deep knowledge of sports, and typically a degree in statistics, mathematics, or a related field. Proficiency with data analytics tools such as R, Python, SQL, and sports-specific software like SportVU or Synergy is highly valued. Excellent communication, critical thinking, and teamwork abilities help analysts present insights clearly and collaborate with coaches and athletes. These skills ensure accurate data-driven decisions that enhance team performance and give a competitive edge.
More about Professional Sports Analytics jobs
What cities are hiring for Professional Sports Analytics jobs? Cities with the most Professional Sports Analytics job openings:
What are the most commonly searched types of Sports Analytics jobs? The most popular types of Sports Analytics jobs are:
What states have the most Professional Sports Analytics jobs? States with the most job openings for Professional Sports Analytics jobs include:
What job categories do people searching Professional Sports Analytics jobs look for? The top searched job categories for Professional Sports Analytics jobs are:
Infographic showing various Professional Sports Analytics job openings in the United States as of June 2026, with employment types broken down into 22% Full Time, and 78% Part Time. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $125,326 per year, or $60.3 per hour.
Sports Data Analyst

Sports Data Analyst

Swish Analytics

San Francisco, CA

Full-time

Posted 12 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.

Duties:

  • Work closely with Data Scientists and Engineers to diagnose and treat data pipeline integrity issues

  • Detect data inaccuracies such as missing, out of range or otherwise incorrect on-field data

  • Source origins of data inaccuracies through data pipeline dependencies and python code base

  • Define data validation tests to flag future game errors

  • Research accurate roster active statuses, primary positions and game participation

  • Validate data changes after logic updates

  • Production model feature deep dives to explain project market lines

  • Clearly document findings

  • Develop intimate familiarity with existing databases and construct metadata references

  • With guidance, support lead Data Scientists in feature development and model analysis

Requirements:

  • 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 compositions of professional and college teams, general gameplay strategies, and typical in-game scenarios

  • Data Extraction, Wrangling and Analysis in Python

  • Strong SQL querying skills

  • Attention to detail

Preferred:

  • Strong Python data management programming skills

  • Data Visualization experience with a user application like Streamlit

  • Deep knowledge of a second sport including football, basketball, baseball, hockey or tennis

  • Exposure to the data science process and tech stack

  • Anomaly Detection Techniques

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.