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Sports Analytics Jobs in California (NOW HIRING)

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 ...

Stackruit Ltd.

Front End Engineer

San Francisco, CA · On-site

$100 - $130/hr

Why Swish Analytics? * Be part of a fast-paced and growing company at the forefront of sports analytics. * Work on challenging and impactful projects that leverage cutting-edge technologies. * Enjoy ...

Bay FC

Head of Data & Analytics

San Jose, CA · On-site

Required : • Passionate about advancing women's sports and leveraging data to elevate performance ... or analytics roles within professional football or elite sports. • Hands-on background with ...

Bay Football Club

Head of Data & Analytics

San Jose, CA · On-site

$140K/yr

Collaborate with sports science, medical and coaching staff to connect workload, wellness, and performance outcomes, incorporating key analytics insights into Individual Development Plans (IDPs) to ...

TOGETHXR

Head of Data & Analytics

San Jose, CA · On-site

$126 - $154/hr

Collaborate with sports science, medical and coaching staff to connect workload, wellness, and performance outcomes, incorporating key analytics insights into Individual Development Plans (IDPs) to ...

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All JobsSports Analytics JobsSports Analytics Jobs in California

Sports Analytics information

See California salary details

$63.7K

$123.7K

$176.7K

How much do sports analytics jobs pay per year?

As of Aug 23, 2026, the average yearly pay for sports analytics in California is $123,685.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,700.00 and $147,000.00 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

What are the most commonly searched types of Sports Analytics jobs in California?

The most popular types of Sports Analytics jobs in California are:

What are popular job titles related to Sports Analytics jobs in California?

For Sports Analytics jobs in California, the most frequently searched job titles are:

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

The top searched job categories for Sports Analytics jobs in California are:

What cities in California are hiring for Sports Analytics jobs?

Cities in California with the most Sports Analytics job openings:

Sports Analytics jobs near you
Infographic showing various Sports Analytics job openings in California as of August 2026, with employment types broken down into 1% Internship, 95% Full Time, 2% Part Time, and 2% Contract. Highlights an 77% Physical, 8% Hybrid, and 15% Remote job distribution, with an average salary of $123,685 per year, or $59.5 per hour.

Machine Learning Engineer

Swish Analytics

San Francisco, CA • On-site, Remote

$160K/yr

Full-time

Re-posted 6 days ago

Job 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 enterprise clients.
The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. They can assist with optimizing the different aspects of the modeling process (Data Validation, Data Visualization, Data Stores & Structures, Feature Engineering, Model Training & Evaluation, Deployments) and improving a variety of Swish products. They will know when to "roll your own" and when to outsource a particular step in the modeling process. They will engineer custom solutions to solve complex data-related sports challenges across multiple leagues.
This position is 100% remote
Responsibilities:
  • Design, prototype, implement, evaluate, optimize systems to generate sports datasets and predictions with high accuracy and low latency.
  • Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow.
  • Build, test, deploy and maintain production systems.
  • Work closely with DevOps and Data Engineering teams to assist with implementation, optimization and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages.
  • Support maintenance and optimization of cloud-native EDW and ETL solutions.
  • Maintain and promote best practices for software development, including deployment process, documentation, and coding standards.
  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.
  • Use extensive experience to build, test, debug, and deploy production-grade components.
  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.
  • Participate in development of database structures that fit into the overall architecture of Swish systems

Qualifications:
  • Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area
  • 5+ years of demonstrated experience developing and delivering clean and efficient production code to serve business needs
  • A proven background in quantitative analytics, trading, or engineering is required for this position
  • Demonstrated experience developing data science modeling systems and infrastructure at scale
  • Experience with Python and exposure to modern machine learning frameworks
  • Proficient in SQL; experience with MySQL
  • Background and/or interest in Rust preferred
  • Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback
  • Strong communication skills when discussing technical concepts with technical and non-technical colleagues

Base salary: starting at $160,000 base plus bonus potential
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 Engineering & Infrastructure Role Data Science Infrastructure Locations San Francisco, CA - Remote Remote status Fully Remote

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