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Sports Analytics Jobs (NOW HIRING)

Swish Analytics

Sports Data Analyst

San Francisco, CA · On-site +1

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

Trading Analyst

San Francisco, CA · Remote

$80K/yr

Company Overview 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 ...

Apply Early

Swish Analytics

Trading Analyst

San Francisco, CA · On-site +1

$80K/yr

Company Overview 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

Send Us Your Resume!

San Francisco, CA · On-site +1

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

Send Us Your Resume!

San Francisco, CA

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 ...

Apply Early

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 ...

Apply Early

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

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

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 ...

Apply Early

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 ...

Swish Analytics

Trading Analyst

San Francisco, CA

Company Overview Swish Analytics is a sports analytics, betting, and fantasy startup building the next generation of predictive sports data products. We believe that oddsmaking is a challenge rooted ...

Apply Early

Swish Analytics

Trading Analyst

San Francisco, CA · On-site +1

Company Overview Swish Analytics is a sports analytics, betting, and fantasy startup building the next generation of predictive sports data products. We believe that oddsmaking is a challenge rooted ...

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Sports Analytics information

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$64.5K

$125.3K

$179K

How much do sports analytics jobs pay per year?

As of Jul 2, 2026, the average yearly pay for 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.

How does a sports analytics professional typically collaborate with coaches and athletes to influence game strategies?

Sports analytics professionals work closely with coaches and athletes by providing data-driven insights that inform tactical decisions and player development. They often translate complex statistical findings into actionable recommendations, such as identifying strengths and weaknesses or optimizing lineups. Effective collaboration requires strong communication skills and the ability to tailor analyses to the team's goals, ensuring that data supports real-time decision-making and long-term strategy. Regular meetings, presentations, and feedback sessions are common to ensure alignment between analytics staff and on-field personnel.

What Is Sports Analytics?

Sports analytics is a field of applied statistics that uses past performance data to provide a competitive advantage to a team or individual player. By using data, an analyst can make suggestions on strategies for a given game, monitor the performance of a player, and provide quick analysis of potentially record-setting activities. Sports analytics focuses on two areas: on-field and off-field. The on-field analysis helps improve the tactics and fitness of players, while the off-field analysis focuses on the business and merchandising aspect of sports. Sports analytics is also used in sports gambling to help casinos and similar companies decide on which odds to offer to customers.

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 skills, a solid understanding of sports rules and strategies, and often a degree in statistics, data science, or a related field. Familiarity with analytics software such as R, Python, SQL, and sports-specific databases is typically expected. Attention to detail, critical thinking, and effective communication help interpret complex data and present actionable insights to coaches and teams. These capabilities are vital for making data-driven decisions that improve team performance and competitive edge.

What is sports analytics?

Sports analytics refers to the use of data and statistical methods to analyze athletic performance, strategies, and business operations within the sports industry. Professionals in this field collect and interpret data to help teams make informed decisions about player recruitment, game tactics, injury prevention, and fan engagement. The insights gained from sports analytics can provide a competitive edge and drive improvements both on and off the field. With advances in technology, the scope of sports analytics has expanded to include machine learning, video analysis, and wearable devices.

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

AspectSports AnalyticsSports Data Analyst
CredentialsDegree in statistics, data science, sports managementDegree in statistics, data science, sports management
Work EnvironmentResearch, modeling, strategic planning in sports organizationsData collection, analysis, reporting for teams and organizations
Industry UsageUsed for performance optimization, game strategy, player evaluationUsed for data reporting, insights, and performance tracking

Sports Analytics and Sports Data Analysts share similar educational backgrounds and work environments, focusing on data-driven decision making in sports. While Sports Analytics often involves developing models and strategic insights, Sports Data Analysts primarily focus on collecting and reporting data. Both roles are essential in sports organizations, but Sports Analytics tends to have a broader scope in strategic planning and predictive modeling.

More about Sports Analytics jobs
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Sports Analytics jobs near you
Sports Data Analyst

Sports Data Analyst

Swish Analytics

San Francisco, CA

Full-time

Posted 5 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.