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Basketball Data Analytics Jobs (NOW HIRING)

Swish Analytics

Data Engineer

San Francisco, CA · Remote

$160K/yr

Company Overview Swish Analytics is a sports analytics, betting and fantasy startup building the ... Basketball, and the ability use your knowledge of the sport to inform your work with complex ...

Colby

Assistant Women's Basketball Coach

Waterville, ME · On-site

$4.3K/mo

Prepare film breakdown and analysis, and present analysis to team members * Plan and prepare for ... data, documents, issues, etc., and respect privacy needs of employees and past employees with ...

Valero Energy

Staff Data Scientist

San Antonio, TX · On-site

Lead the development of solutions for complex analytical challenges across all business units ... Basketball Facilities * Onsite cafeteria open for breakfast and lunch * Sprawling campus with ...

Valero Energy

Staff Data Scientist

San Antonio, TX · On-site

$120 - $160/hr

Lead the development of solutions for complex analytical challenges across all business units ... Basketball Facilities * Onsite cafeteria open for breakfast and lunch * Sprawling campus with ...

Valero

Staff Data Scientist

San Antonio, TX

Lead the development of solutions for complex analytical challenges across all business units ... Basketball Facilities * Onsite cafeteria open for breakfast and lunch * Sprawling campus with ...

Swish Analytics

Trading Analyst

San Francisco, CA · On-site +1

$65K/yr

... analytics data products. We believe that oddsmaking is a challenge rooted in engineering ... Passion and intimate knowledge of the NBA, NFL, MLB, NHL, and NCAA Basketball + Football * Strong ...

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Basketball Data Analytics information

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$33K

$81.5K

$140K

How much do basketball data analytics jobs pay per year?

As of Aug 12, 2026, the average yearly pay for basketball data analytics in the United States is $81,518.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $96,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a basketball data analyst?

To thrive as a Basketball Data Analyst, you need strong statistical analysis, data interpretation, and basketball-specific knowledge, often supported by a degree in statistics, mathematics, or a related field. Proficiency with analytics software and programming languages such as Python, R, SQL, and visualization tools like Tableau is typically required. Attention to detail, critical thinking, and effective communication are vital soft skills for turning complex data into actionable insights for coaches and teams. These abilities are essential for informing strategic decisions, enhancing team performance, and providing a competitive edge in basketball operations.

What is basketball data analytics?

Basketball data analytics refers to the use of statistical and computational methods to collect, analyze, and interpret data related to basketball performance. Analysts use data from games, player tracking systems, and historical records to identify patterns, evaluate player performance, and inform coaching strategies. This field helps teams gain a competitive edge by making evidence-based decisions regarding player acquisitions, game tactics, and player development. It combines knowledge of basketball with expertise in statistics, programming, and data visualization.

What is the difference between Basketball Data Analytics vs Basketball Operations Analyst?

AspectBasketball Data AnalyticsBasketball Operations Analyst
Primary FocusAnalyzing data to inform team strategies and player performanceOverseeing day-to-day team operations and logistics
Required SkillsData analysis, statistics, programming, visualizationTeam management, communication, organizational skills
Work EnvironmentData centers, offices, sports analytics departmentsTeam facilities, arenas, administrative offices
Common EmployersNBA teams, sports analytics firms, consulting agenciesNBA teams, sports organizations, management firms

Basketball Data Analytics primarily focuses on analyzing data to improve team performance, while Basketball Operations Analysts handle the broader operational aspects of team management. Both roles often collaborate but differ in their core responsibilities and skill sets.

How do professionals in basketball data analytics typically collaborate with coaches and players to influence team strategies?

Professionals in Basketball Data Analytics work closely with coaches and, at times, directly with players to translate complex data into actionable insights. They often attend team meetings, present analytical findings in understandable formats, and provide real-time data during games or practices. Effective communication is key, as analysts must bridge the gap between statistical outputs and on-court tactics, helping coaches adjust strategies and optimize player performance based on data-driven recommendations. This collaboration fosters a culture of innovation and can directly impact game outcomes and player development.
More about Basketball Data Analytics jobs
What states have the most Basketball Data Analytics jobs? States with the most job openings for Basketball Data Analytics jobs include:
What job categories do people searching Basketball Data Analytics jobs look for? The top searched job categories for Basketball Data Analytics jobs are:
Basketball Data Analytics jobs near you
Infographic showing various Basketball Data Analytics job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $81,518 per year, or $39.2 per hour.

Data Engineer

Swish Analytics

San Francisco, CA • Remote

$160K/yr

Full-time

Posted 21 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 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 2+ 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

  • A strong interest in sports and sports betting, with an emphasis on Tennis. An understanding of US-based sports including the NFL, NBA, MLB, NHL, College Football, College Basketball, and the ability use your knowledge of the sport to inform your work with complex datasets

Base Salary: Starting at $160,000 - 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.