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Sports Analytics Jobs (NOW HIRING)

Swish Analytics

Data Engineer

San Francisco, CA · On-site +1

$145K/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

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 next generation of predictive sports analytics data products. We believe that oddsmaking is a ...

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 · 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

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 ...

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 ...

SIG Susquehanna

$150 - $200/hr

We specialize in geopolitical and sports analytics across the globe. This is an opportunity to build out a next gen sports trading system within an early-stage initiative focused on influential ...

Leland

Sports Management Coach

$17 - $22/hr

... sports analytics, sports law, and brand development. Coaches also help students build these capabilities through consistent, practical skill building, and support the career side of the journey ...

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How much do sports analytics jobs pay per year?

As of Sep 7, 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.

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 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 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.

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 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.

How do I get into sports analytics?

To pursue a career in sports analytics, develop strong skills in statistics, data analysis, and programming languages such as Python or R. Gaining experience through internships, building a portfolio of projects, and understanding sports data sources can improve your prospects; a background in sports management or related fields is also beneficial.

What are careers in sports analytics?

Careers in sports analytics involve analyzing data to evaluate player performance, team strategies, and game outcomes. Professionals typically use statistical software, programming languages like Python or R, and possess strong knowledge of sports and data analysis techniques. Common roles include sports analyst, data scientist, and performance analyst, often requiring a background in statistics, computer science, or related fields.

Will sports analytics jobs be replaced by AI?

Sports analytics jobs involve analyzing data to inform team strategies and player performance, requiring skills in statistics, programming, and domain knowledge. While AI tools can automate data processing and generate insights, human expertise remains essential for interpreting results and making strategic decisions, so these roles are likely to evolve rather than be fully replaced.
More about sports analytics jobs

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Cities with the most 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 Sports Analytics jobs?

States with the most job openings for Sports Analytics jobs include:

What job categories do people searching Sports Analytics jobs look for?

The top searched job categories for Sports Analytics jobs are:

sports analytics jobs near you
Infographic showing various Sports Analytics job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 94% Full Time, 3% Part Time, and 2% Contract. Highlights an 79% Physical, 6% Hybrid, and 15% Remote job distribution, with an average salary of $125,326 per year, or $60.3 per hour.

Data Engineer

Swish Analytics

San Francisco, CA • On-site, Remote

$145K/yr

Full-time

Re-posted 18 days ago

Job description

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 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
The Swish Analytics team is seeking Data Engineers based in Europe to have a direct impact on the infrastructure and delivery of our core consumer and enterprise data offerings as well as helping support our coverage of non-US sports. We're a team passionate about accurate predictions and real-time data, and hope you find satisfaction in building new products with the latest and greatest technologies. This is a remote position.
Duties
  • Support production systems and help triage issues during live sporting events
  • Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production
  • Build new sports betting data products and predictions offerings
  • Integrate large and complex real-time datasets into new consumer and enterprise products
  • Develop production-level predictive analytics into enterprise-grade APIs
  • Contribute to the design and implementation of new, fully-automated sports data delivery frameworks

Requirements
  • BS/BA degree in Mathematics, Computer Science, or related STEM field
  • Minimum of 4+ years of demonstrated experience writing production level code (Python)
  • Proficiency in Python and SQL (preferably MySQL) Demonstrated experience with Airflow
  • Demonstrated experience with Kubernetes
  • Experience building end-to-end ETL pipelines
  • Experience utilizing REST APIs
  • Experience with version control (git), continuous integration and deployment, shell scripting, and cloud-computing infrastructures (AWS)
  • Experience with web scraping and cleaning unstructured data
  • Knowledge of data science and machine learning concepts
  • Professional working experience with MLB or NBA data

Salary: Starting at $145,000 - DOE
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 Engineering Locations San Francisco, CA - Remote Remote status Fully Remote

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